Agreed with you, with Gen AI the data analytics works would get mostly automated while the DA is moving just for a entry point into data industry and DE or DS will be the next step to evolve and further to ML and AI...
But what if as a Pakistani I get a remote Data Analyst job? Even if my annual salary is like 30K Annually I am earning a fortune. In just 10 years I will have enough money to become a Big business man in Pakistan.
There is so many "data analyst' who do not undurstand statistics, that's what probably make it "silly" job. Do any of you guys even check if the data is independent before doing any statistical analys? Do you even did a decent statistics course?
Not everyone desires to be a data scientist. If you love data analysis and visualization, this is still an excellent career path. I'm making 6 figures in my role as an analyst using just Excel and it's low stress, great hours. I can't complain
@andiuptown1711 yes, you have to be comfortable speaking to others. I do have lots of heads down solo working time. But since I'm the only analyst, I'm the go-to data person in the office. I have to report out in meetings with senior leadership. and sometimes do presentations to the whole office on interesting findings
For those who got a little frustrated of pursuing Data analysis career: Keep in mind even if it's not a tech role eventually with the right skillset and experience it will lead to one (Data Scientist/Architect). When it comes to competitiveness in the market, tell me which career is easy and noncompetitive, go any finance role there are tons of applicants for each position (highly depending on location :). Last but not least pay is still more than average salary in U.S I guess so keep your head up and go for it ))
My question is would I be able to work %100 remotely? If so, idc about prestige. If I can work and live somewhere else where the US dollar can go further, then I want it.
l Agee with you. lf we say there is an oversupply of data analysts what about accountants or those in social sciences. lt's not easy to be disclplined and consistent until one becomes an above average data analyst. it's not everyday you meet someone who knows filtering using panda or who can make a dynamic dashboard using power BI..
A harsh reality for me as a data analyst, 20 year veteran, is the fact that businesses often have non-technical managers who manage data departments. I've had some seriously stupid managers who have had a few spreadsheet skills and they think they can manage an entire data team. I have seen literally hundreds of thousands of dollars wasted due to these bozo managers who primarily exist because of super size egos and bluffing their way to the top. Case in point, I was ready to build an automation for a billing department and the COO killed the project because he couldn't understand it. The automation would have saved at least $50,000 per year. Welcome to Corporate America!
Based on my limited experience, you’re so correct! I have been interviewed by managers of data departments and they really only were familiar with basic excel and some Power BI. I was so surprised, because I have done a ton of research of my own and thought I had to learn python, SQL, etc. I’m sure those skills are definitely valued, but based on my limited experience, they didn’t require many of those skills.
For them to understand, you kinda need to have a set of proposals in beginner vocabulary. I know what you mean. I'm trying right now. I started by showing them the magic of cloud and remote access. Hopefully, we can work our way up from there. Life for the whole corporation would be much more convenient if it upscaled their data management and tech utilization.
I actually appreciate knowing that Data Analyst is used as a transitional role for a lot of people, that means for those of us just starting out, we will EVENTUALLY get in, because the market is constantly turning over. (Gotta find those silver linings)
I feel like data analysis might become a skill many employees will be required to have regardless of their field. With the increase in automation, domain knowledge and the ability to use these automation tools might just be what’s needed. Also, python is being integrated in Excel now which is used in nearly every role
It should be like this. Data analysis should be considered as a tool, like ML and other technologies. In my opinion, it is not possible to be a stand alone data analyst or scientist, he/she should be an expert in a field with those skills.
Non-data analysts make for really poor data analysts IMO. If some random corporate employee with a history degree thinks that money should be spent on X because of some python analysis they've done in MS Excel, I don't think I'd put much hope into it.
@@Gilbert942 I'm an actual data analyst and I was told to work with a guy who had spent 20 years working in Denmark on the science of pig feed. But when I gave him some data on the economics of pig farming, he spent months making a complete mess of it, even though he had been hired as a data analyst, who happened to have a history in pig farming. No amount of subject knowledge was going to help this guy with data analytics. I have a dozen more examples where an expert in one field thinks they can have a go at data analysis and it always ends the same way.
It is very easy to be a data analyst but very hard to be a good data analyst. 1) The field makes it very easy to make mistakes; the automated checking in software development doesn't apply here 2) A good data analyst needs to have an active engagement with the client, not simply doing what is requested but producing something better.
Isn't that the same for every field ? A normal software engineer would deliver what is requested, a good one will deliver something better over what is requested.
Part 2 is very dangerous. How do you know you are delivering the right thing? After getting burned a few times I only delivered what was requested. If you are working on contract an increase of scope means there should be increase in fees and an extension of deadlines.
@@pedrolopez8057 Yes, often I will have to deliver the request as stated and then have a discussion of what else I could do. If this is on a contract the contract may very well need expansion.
As a data analyst, at my company my entire team is so grateful we are NOT considered tech / IT: that team is the first to be 'streamlined' every few years because of their high salaries, so there is constant anxiety on that side of things of "is this the day they think there are too many of us?". Keep the extra money, it doesn't buy peace of mind!
i’m really looking into a degree apprenticeship i will have A level qualifications very soon is there any social media’s i can enquire about with you? ( for instance instagram?)
I’m loving that perspective because there are so many videos talking about Tech downsizing being a huge problem every year. The idea of the imminent layoff makes wanting a tech job discouraging. I appreciate the positive words 🙏🏼
The hardest thing about it not being considered a tech role at my company is that I'm always running into permission and access issues for things that we should've had access to by default if we were considered part of the programming teams or something. My boss is constantly fighting with management trying to explain to them why my role needs permissions to certain systems.
Many think that becoming a Data Analyst is just a matter of learning a bit of SQL, Python, and a viz tool. Hence, the "less prestigious" label. I've been in the fields for some years and I can tell there are infinite "shades" of being a Data Analyst, some are more tool-oriented, some business-oriented, some engineering-oriented. There is no one definition that fits all. A "complete" data analyst, one that can translate business needs into data insights and ultimately business decisions has more value than any individual tech contributor (including DS). Some companies have realized that and are willing to pay top-notch salaries for the job. The problem is that not many DA have the skills for those jobs, mainly because the large majority of DA perceive the role as a pure tech job while in reality the amount of hard skills needed is at least equal to the amount of soft skills. Being a DA is not an easy job and people approaching this career should know that to succeed it takes a lot of pain and stepping out of their comfort zone. That's why many people leave this career path at some stage.
Good post. This is a great take. I was a data analyst for years, but as you mentioned slotted into the engineering side.... Eventually I moved into a data engineering role, but what you say IMO is fact.
I think you answered the question on why pay for data analyst is lower than software development: there are plenty of people in the field. BUT I would say to anyone in the field the way you add value is not through analyzing data it is by delivering actionable insights. Directly influencing business decisions is just as powerful as developing products. In fact, consider how to create data products at your company. Lots of options to demonstrate high value!
Absolutely right, if you have business accument and you know how to fulfill stakeholders expectations, you will be adding a lot of value to your roll..
I agree and disagree at the same time. Those that present well definitely have a better career path, but the only thing that really matters is if the data actually says what it says. If a director is being paid the big bucks, it stands to reason they should have the ability to understand dry data sets, and not need some jazzed up infographic to make the correct decision for the company
I’m a former data analyst. I’m very glad I’m now an engineer instead. One thing I would have added to this video is that data analysts are often too much on the business side in terms of interfacing with stakeholders and attending a lot of stupid meetings. That was very noticeable when I moved over to engineering where I don’t really interface with stakeholders or attend many meetings other than stand ups or meeting with other technical teams
Right. So much DA work is stakeholders wanting MUH DASHBOARD. And reports. Dashboards and reports and meetings are useless. They are for people who don't want to read. Nothing against DAs but that's what gets forced on them in the role.
The actual harsh reality, based on my personal experience. I have a Doctor of Physical Therapy degree and years of clinical experience. I have taken data analytics courses at the Masters level at a well known university. I have also done my own learning through Udemy, Codecademy, DataCamp, etc. I have completed projects in Tableau, Power BI, and SAS studio and visual analytics. My goal was to become a healthcare data analyst. However, after >200 job applications, I feel I should move on. The harsh reality is that there are millions of people jumping on the bandwagon. Competition is extremely fierce apparently. Even with an advanced degree and actual industry knowledge and training, I still can’t seem to find any hiring managers who believe that my unique skill set would be an asset.
I’m a health informaticist by qualifications (I have a masters degree in health informatics) and although I’ve had experience on the clinical side of things (kinesiology degree, volunteer hours, internship, etc.), my biggest obstacle in finding a role as a clinical data analyst is elitism in the medical field. Simply put, I’m not an MD and therefore there’s no guarantee I’ll understand the context of the data (even though I do). It is indeed extremely difficult to find a job in this field but I do believe it’s a worthwhile field to be in to advance healthcare delivery. I hope you find something soon.
Yup so I transitioned from Data Analyst to Data Scientist and hopefully get to ML engineer soon. But what I also noticed is that people who work too long as a data analyst are stuck there. Especially in a big corp where they make you learn a very specific tech stack that you can't transfer over to other jobs.
I crossed over from DevOps and I can say that things in the Data World are just as difficult if not more because whatever your role is in the data world it involves more interaction with consumers of data and their requirements as well as the technical know-how on how to deliver it even if that is SQL or using Pandas in Python. With that said, there's also such a thing as data maturity and organizations that are low in data maturity tend to have the highest aspirations, meaning, they want things that can't be delivered within the current technological stack and this why astute people may start off as analyst but have to become data engineers, and DBAs, and still get paid an analyst salary.
I mean, if you can still pay the bills, like what you're doing, and don't care about elitists judging you, then by all means stay a data analyst! The great thing is the skills you gain from data analysis transfer into so many other careers, so you won't be stuck, so I think it's a great path that opens a lot of doors! At least, I hope so, cuz that's why I'm trying to do!
I'm a data analyst and one thing I've found is the sheer number of people who don't have a clue what a data analyst is (especially HR). Outside of the tech and engineering department in an organisation, people think all data analysts do is create a few nice graphs here and there out of thin air. They have no idea about formulas, the maths behind calculations, rates, time series comparisons or anything comprising the graphs. They have no idea about the technical skills it takes to create automated dashboards (in whatever platform) and how shitty of a state most data is in.
Anna, your problem is that these terms have been getting invented and thrown around like confetti to mean "whatever it needs to mean right now to get a job". It's like "Data Scientist". I have been in IT 40+ years. No one can explain to me to my satisfaction what a "Data Scientist" is. Our colleagues on the business side of the house have every reason to not take us seriously when we call ourselves "Engineers" and "Scientists". We are neither of these.
@@Peter-Jones I think my problem is that no one outside IT knows what a data analyst does. That's what I said in my comment. Call me analyst, scientist, data engineer, data wizz, whatever. People still wouldn't know what we do.
@@annafidler9011 Hi Anna, my comment is pretty old, thanks for getting back to me. My point is that people on the IT side make up all these terms and then use them to the business and the business people have no clue what they mean. When people ask me what I do? I say "I help companies make a lot more money" and leave it at that. Every business person knows what that means. When they ask me about my track record I repeat some results from some clients. I would never talk to a business person about anything technical. Not only do they don't understand? They don't care. I stopped doing that 30 years ago. LOL!
As a beginner, I loved the video to the end seemingly because of your realisitic approach towards explaining the industry scenario as a whole. However, I'd like to make a request at the same time which is to make a similar video like this only on DATA ENGINEERING / DATA SCIENCE. Would love more insights on the harsh reality concerning these career paths. Lastly, love from Bangladesh
I feel like part of the reason why data analysts arent viewed as tech roles is because there are many data analysts roles where all youre doing is working with Excel. Many of the data analyst jobs I got did not require me to use any programming beyond maybe some Power BI stuff. There is a big mismatch between the skills that data analysts learn in data analytics programs and what is actually required to do the job.
Moved into the data analysis path just about a year ago after completing a data science bootcamp. The application/interview process when you're fresh in the field can be daunting (had something close to 300 applications sent and 7-8 interviews over a 4 month span before I took an offer), all your points are solid though. I would say to anyone seeing this and considering making the move, go for it, just trust the process!
Oh my god breaking the barrier to get in is so hard. Ive been applying for around a year (to be fair i only graduated college in May) and finally just got an offer that I accepted. Hundreds of applications sent out, hundreds of hours on LinkedIn. Its draining. I feel good that I got my lucky break but now Im worried about getting laid off and having to go through it all over again
Bringing a bit of a different angle or perspective to this. I am an aerospace and mechanical engineer specialized in the areas of propulsion and structural analysis and design. On my side of the barn, in the aeronautical and aerospace industry, I have yet to encounter someone with the skillset that Data Analysts bring to the table when it comes to taking all our data and not only provide great insight into the results but also automate our processes. Of course I am a big advocate on growth and development in life, but if you are thinking about starting/staying as a Data Analyst DO NOT think that your skills and work is meaningless.
I was recently promoted to a resource manager, and a couple days in, I realized it's actually a full on data analyst. I'm actually looking forward to it as the position is fairly laid back, has a lot of improvements that can be made, and I'm given quite a broad canvas as to what I can do.
A tip for entry level data analysist: try to get into some narrowly specialised fields where data analytics is used. You'll gain 1-2 years of experience and can move on to other industries. Just don't miss the sweet spot when you already have a good understanding of processes involved, but still at a junior enough level to move on 😉
@@rochellec Supply chain. Literally everything there now is data oriented. Bonus points, if you can get into some more specialised supply chain branches like aerospace - easy way to get into Ryanair or big players on the market like Boeing/ Rolls Royce/Collins etc.
@@Proph3t3Nhello, I have a Bachelor’s degree in transport management, and I’m taking data analysis courses at the moment… what do you think will be a good Master’s degree course I can do
@@rochellec My first job was in clinical research as a "statistical programmer" but it's really just analytics work. It's lucrative but right now is a tough time for the industry and I expect layoffs. Clinical trials are funded with loans, and there are just less contracts out there to win with the higher interest rates. If you're in school and have some time before graduating, you might want to keep an eye on it in case things improve. It usually requires a quantitative degree of some sort, like computer science, engineering, mathematics, or statistics. It uses SAS and if you stay too long might get pigeon-holed, but it's a good way to get your foot in the door and get the first job.
Low barrier-to-entry jobs that pay reasonably are a great thing in my estimation even if they come with a bit of a growth cap. The reality is that you can jump over that cap if you are willing to keep growing and learning. For me, machinist was the low barrier job that allowed me to earn enough to go to engineering school and jump over the pay cap that would have come from staying in a machinist role.
I also appreciate how often it gets you quite close to managing execs early on in your career. So you can see the higher level in a company. The main downside for a young person is you're then stuck with people who are a lot older than you.
data analyts make less than data scientists for a good reason. An actual data scientist is skilled in many levels math including stats, linear algebra and some calculus. You will not find many data analysts with those skills. a good data scientist brings more to the table; thus, they are paid more. its the harsh reality. SQL is absolutely a coding language. the pay for a data analyst is going to vary. Believe it or not there are some data analysts who dont know SQL or python, they live in excel so there pay might be less than someone who knows sql and python. it all depends on your skill set and what you bring to the table
confused why people care about if someone looks down on them. I could care less what someone one in a different career path thinks about my choices. If the person looks down on me is NOT paying my bills, then why is this even an element this "harsh reality"??? So confusing...
Wow, I watched this video last night and loved it! Then today I am working on the Google Data Analytics Program on Coursera, and there you are talking about how to deal with imposter syndrome! I loved that too, and it gave me the motivation to continue my networking efforts, even though its not my forte. There is power in how open and honest you are. Thank you for providing so much effort and wisdom to help those of us who are in a similar place to where you started from!
You have to have other domain knowledge and couple that with data science/analysis. Knowing how to gather, clean, analyze, display, or synthesize data means nothing if you can’t interpret the data. Data is a raw input, your work as an analyst or scientist is to take that raw material and turn it into an insight. You have to understand the data and what it means to be valuable and paid accordingly.
Domain knowledge isn't as hard to gain, also thats why Subject mater experts exists on data teams and tech teams. You can ask every developer, data scientist, data engineer/analyst to know everything about their field + domain knowledge
The level to entry is very difficult. Thankfully I leveraged getting my foot in the door into a tech company and was able to transfer into an Analyst role. That being said, the job market and search is flooded with people trying land Analyst roles that I’ve see jobs low balling salaries because they know someone will take that pay to just gain experience. Hopefully this changes and I still think Analyst roles are great but just know it’s not something you can easily get into. You’re going to have to stand out in some capacity.
As a data analyst, you can get lots of exposure to an industry you join. Problem is most of the time this opportunities occur because the company just realized they have lots of data but hasnt been utilizing/managing it.
This may be an unpopular opinion, but honestly, any pay higher than 70k would be a luxury to me. I dont NEED to make more than that, sure, if you're planning on living somewhere that rent or mortgage is like $4,000 than yeah i can see your issue, but i'm not one of those people. where i live/ where i intend on living, is not that expensive. and its kind of crazy to me that anyone making 68k+ would be so unhappy with that pay. Like, yes, is more better? yeah, but i would LOVE to make 68k right now lol
". I dont NEED to make more than that" Pay is not based on an employees needs. It is based on compensation for the skills required. You are welcome to accept a low pay salary as a young person but what a skilled, brilliant person can bring to a company is not overlooked by companies who understand the benefit they receive and the fact that their competition might pay even more. Those are the statements of a very young person without children or a mortgage. 70k is a very low salary for someone who has a mortgage, one or more children, commuting overhead and a life to live. Enjoy your youth! I wish I was young and carefree. It was a fun time.
Everyone grows in their career, if you have data analytics in your resume it will definitely be a huge plus if you are moving up in managerial positions.
Fundamentally, to get paid more you have to sell or build the core product, or you lead the team that does so. Data has a lower cap because it's an advisory service (note: the cap does not exit when the core product is ML), and amongst the advisory services it pays the highest because the skills are so specialized. I agree that it's easy to call one's self an analyst, but it is exceedingly difficult to be a good analyst. Moreover, to your comment, many of the good ones leave - not because of a dearth of opportunities for them (they have options) - but because they choose to transition from being the sage council to leading the troops on the field.
1. Most data analyst promote themself to data scientist at some point with some upskilling. And they should do. 2. Yes there is a surplus of data analyst, whenever there is a demand people move in that direction. That doesn't mean sometime should stop 3. SQL is very important for any data person. 4. A data scientist should be able to do all work of data analyst in today's day. 5. You can't stay in one position for rest of your life, you have to grow.
If you like what a DA does and become good at it, the $ will come. Keep in mind: 1. DA not a tech role and pays less $$ compare to others - AI is changing almost everything as we are talking; even for Data Scientist/DS, Data/Software Engineers/DE/SWE, ... However, having domain knowledge and strong foundational coding & soft skills helps. - Depends on the company 2. Move on to other roles such as DS/DE - Are you willing to constantly learn off the job to keep up with the skills stack? - Competition is also tough 3. Check out Analytics Engineer
Very nice of you showing the harsh part of being a data analyst. The most important point that really got me surprised was the fact that is not considered a tech role. I really believed that it was my chance to have an IT occupation. 😢
You are not wrong, finding a job as an entry data analyst has been a pain. And um still looking. Most companies are looking for people with a degree or 2 years minimum experience
@@ryuhayabusa3540 Right now the market is just crazy. I have a master's degree in data science, with 5 years of experience in data analysis and data science. I am applying for any job in data science and data analysis, still cant get any.
In the company I work for, I had the opportunity to cross path with data analysts. I'm a data engineer, and what I can say about your question of "How is it not a tech role?" is that being a data engineer the focus of our job are the technical parts. Data analysts deal a LOT with clients in their daily basis, it's closer to business than tech. Writing in SQL, using pandas, it doesn't even scratch the surface of how hard it is to deal with infrastructure.
Your comment is subjective, she's not just talking out of her ass, she was Data engineer before she became a Data scientist, then currently a Data Analyst
Thank you for your insights! Data analyst does age out and has a cap of their career growth. You do need the passion to be in this job family. Don’t do it because it’s cool or trending.
I've just started learning data analysis from coursera. It seems like data analysts are considered like dentists of the tech. But as far as I researched, there is no other entry way to data scientist/engineer or ML engineer for us trying to start carreer from internet. You just have to keep studying while you're working.
I really wanted to become a Data Analyst by pivoting from my cost accounting career. After doing a lot of research I come to find out that I didn't feel like the field had "staying power" long term, and would likely get integrated into other similar positions, but retaining those positions core responsibility. I personally think that learning Data Analytics will make me a much better Cost Accountant which will add way more value to a company than just knowing the Data Analytics portion alone.
After years of experience and research, I have arrived at the same conclusion. While conventional professions like accountancy, planning, and purchasing offer a certain level of security, they can be greatly enhanced by incorporating coding for improved analysis and automation. It's possible I may be mistaken, but this integration holds the potential for significant advancements.
BRO literally the same! Have been doing cost accounting for almost 3 years but I don't know if the is a way up or even out.. because we are somewhere between an accounting and finance
Definitely. Microsoft’s vision is for empowered end users: there are accountants out there doing stuff with Power Pivot, Power Query, Power Automate that is awesome
I am a truck driver and I am getting into data analytics as a stepping stone, I have no background in computers so this seemed to be the fastest way to get in the door. Once I get established here I will go in another direction. I appreciate your video I learned some things, but I have other goals in mind
My wife has to do SQL in various jobs, and she's a volunteer coordinator. Her political science classes required it too. SQL is just a tool to get to data you need. Python though, that's a bit more of a higher level skill. However, Python is rarely used in massive or complex systems. Its usually a script to do specific small tasks, so perhaps that's the thinking?
The difference in salary is due to the skillset difference. Data analysts deal primarily with descriptive analysis of data and as the video describes, anyone can learn to do this. Data scientists normally have postgraduate degrees and are concerned with predictive and inferential modelling and statistics. Proper inferential statistical skill, and understanding research design and sampling to contextualise your analyses requires a lot of formal study, and so is much rarer. Hence the higher salary.
I think your second point is the most important one. There may be some very well trained and technically minded people calling themselves data analysts. And there are others who really have no clue and are more interested in building pretty dashboards. And most of the tools and processes they use do not follow the same rigor as professional developers. Such simple concepts as source code control and update tracking, release management and version control, formal bug tracking, design reviews .... Basic table stakes for developers, and largely unheard of by data analysts. And a lot don't really have a solid background in statistics, so they present very misleading things (like representing crazy skewed data with nothing more than an average, or confusing correlation with cause, or taking the average of a bunch of averages, .....). I think they can play an incredibly important and valuable role, but sloppy, misleading, unprofessional data analysis can be devastating. And most people recruiting and hiring have no clue as to how to assess the candidate's skill.
Very interesting feedback, thank you for that. I also recently stepped into Business Intelligence as a Data Analyst without prior experience. So I would like to share my experience as a Junior.. I fast tracked HTML, CSS, JavaScript, PostgreSQL, GA4 and GTM knowledge for my job role, but this was just the foot in the door (I do have other responsibilities outside of Data Analysis). It's been very challenging and fulfilling so far, problem solving has been a very big part of the experience and I think this can often lead to Imposter Syndrome (Like you mentioned in your Data Scientist video). Having to dig, and dig to find an issue not necessarily with one table or flow (tableau), but a whole bundle of them, and how they feed into other departments, can definitely lead to someone feeling like they are inadequate or overwhelming for a beginner. However, stick in there Juniors, it gets better over time as your confidence, knowledge and skills grows. Take every day as a challenge, celebrate every success and learn from every failure and then things will to fall into place. At least in my experience.
There needs to be some hope for those of us who've been unemployed for several years. You can't just tell people competition is insane. Tell all the people trying to get into this field to seek out other another field.
I am an entry level data analyst in India. What I did to find this job was I enrolled in a analytics training institute that promised job assistance. I got very lucrative salary package at a local company. To give you an idea, its four times the average package what jobs were paying in campus placement of my college. Most of my peers of our batch got half of my salary package.
Thankyou for the valuable insights. You saved me from the unreal expectations that I had from this job role. Please make a similar video on getting a certified in AI for people with non tech background. Thankyou!
I was looking for a career change and data analyst was what I was considering. Thanks for your valuable advice. I will look for something else or stay in my current job.
"Anyone and everyone can become a data analyst" - no, they cannot. You have to have a mind for numbers, formulas, relational databases, and tables to be data analyst. 95% of the people I've worked with either outright could not be a data analyst, or they have expressed disdain for the day-to-day tasks a DA has. Likewise, I could never do the job of a graphic designer, or content editor, etc. because I have no mind for it. You CAN be a data analyst if you have the mind for it but have not attended college, that much is true.
I from the Netherlands, I'm working as data analyst for 3 year and i making more then 68k per year, think depends from which country and for the company that you are working for you can grow and earn good money
Hi. Just wanted to say hi because you're a data analyst from NL. I'm an analytics engineer, and my job recently sent me to Utrecht for some work over there. It was F-ing AMAZING. I loved that place so much. I've been to cities all over the world, but it was love at first site in Utrecht. I'm trying my hardest to figure out a way to live there. It only makes sense as my favorite color is orange. Have a good one
So I was one of those people who did both DS and AS. I think the thing that differentiates AS from DS is that as a DS we are expected to code in python etc and know all the math stuff whereas an analyst is usually not expected to code in python, or if they do its viewed as "extra" or nice to have. This is why an analyst is viewed as a junior data scientist. Also, SQL is not considered coding because you can't do stuff like loops, etc easily in SQL (you can but its not easy or intuitive or efficient from a code standpoint). For me, i create my datasets using SQL queries, but the minute I want to do any type of summary statistics/analysis/looping operations, I move into Python. This is more efficient. If you are an analyst that is coding in python daily and using machine learning and understand the math behind machine learning then you have graduated to a data scientist and need a pay raise!
Interesting to learn the differences between the job groupings. Though does make me feel better about my decision to go to school for a Data Science position. Thanks for the free book link, the more resources the better!
Thank you so much for being real and giving us the truth! I really appreciate your honesty and the way you approached this subject. I'm one on the many people who are breaking into a role as a data analyst to use it as a stepping stone, and this video has actually strengthened my resolve in choosing this career path. I think at some level, I already intuitively knew about these challenges, but hearing someone with experience just give me the truth in such straight forward way was really refreshing. That's a large reason I'm working so hard to move into data sciences; I care a lot about the truth. I want to understand the world around me in a meaningful way, and use that understanding to help people. Thanks again for a straightforward, honest, and informative video!
All depends on your organization and experience. I’ve known data analysts in my location (Southeast US) who make six figures, and some who make $60k. If you’ve been in the biz a while, and you have a proven record of finding simple, elegant solutions for complex business problems (and can effectively communicate to stakeholders), you’re good, salary-wise. If you just run reports all day and send messy CSV files to stakeholders, you’ll stay in that lower salary range. TLDR- this is a good profession, with a lot of potential, for the right person. If you maintain a mentality of continuous improvement, be creative, learn to communicate, and upskill (sql, python, etc), you’ll be fine. No shame in the data analyst game. - a data analyst 😘
It depends on the data maturity of the team/company. A lot of data scientists struggle to show business value whereas reports, dashboards and decks are always going to be needed. Data engineering is the most critical but doesn't really involve interacting with the business which is less interesting for some people.
Outside faang, most "data scientists" do the same job as data analysts do. Most companies don't need complicated ETL processes and AI/ML. The goal is just giving access to the information, cronjobs and dataviz tools can do that.
You answered your own question!!!! That's why the position may not be considered a tech role because you don't need qualifications. Many people get into IT roles of all kinds with no qualifications and their productivity and attitude varies greatly. In other professions like engineering, architecture, radiology, physiotherapy, geosciences etc need qualifications and a certain standard and foundation.
I've been applying for 6 months to become a data analyst. I improved my resume, started a portfolio, reached out to recruiters, did some networking and still nothing but rejections. I wish I didn't have to feel like I need my hand held to get in the door. I think the market is too saturated right now with too many required skills or software knowledge. I don't know what to do anymore besides continue to add more skills
I shifted to data analysis career from my finance job early in my career. I've worked as data analyst for 3.5 years and already outgrown my job. Now I'm planning to become Data scientist or Data engineer. In the long run, if everyone studies data analysis tools, then I may be working as a finance data analyst since I have a CFA degree. It's my backup plan.
6:00 LOL I just got promoted to Senior Data Analyst last month 😅 I'm not thinking of switching careers though, I like it where I am, nice people, WFH, little stress...
Thank you for the video and insights. I think you answered your own question about the pay disparity between Data Analysts and other Data Engineering/Science roles. The barrier to entry for Data Analyst is low and the number of Data Analysts in market is high. Supply and demand.
An issue: Some higher Ups want to see 'certain numbers' with 'certain values'. If they dont see it 'your' Numbers are Wrong. Your Metrics maybe 100% Correct but that is NOT whatthey "Want to See." This Must Change...
If you don’t love messy data, this job is not for you. Don’t expect instant 6 figures with online/youtube certifications while there are ppl with valid 4 yr degrees and experience probably in CS or Data Science. All the companies I worked for, DAs are considered as tech role, however, salaries can vary based on the experience and degrees, don’t know what she’s talking about. Trust me, managers know from the point of interview that how much experience the person has and how much can deliver, and prefer tech experienced person for a reason. The only reason one may select a RUclips certified one with exaggerated resume because they are understaffed and/or in dire need of a helping hand. She just expressed her frustration through her bad experience which does not cover the entire market.
I don't understand why you ask: "Why data analysts are not paid the same rate as tech?" when in the next section you state that data analytics has a low barrier to entry. This is your answer: if most ppl can learn essential SQL in a week, why would you pay more for that? SQL is no C++. SQL is no Bayesian inference. This is the answer.
Most jobs still require bachelors degree. Cant just get a job in 1 week like you're implying. Even to get a certification can take months but your chances are low unless you have a degree first.
thank you so much for the clarification. studied business management, transitioning into data analyst. It will be hard like you mentioned, but trying to get there!
This is the best video on this, as a data analyst -> data engineer -> data scientist. I would have saved years of time if this video existed 10 years ago!
I have been in QA for 25 yers and I share many of the same skills. You can easily transition to a QA Data role validating query results and creating your own stored procedures to test results of queries vs the front end code of web applications.
Absolutely True, But can you share some insights on how a fresher can make himself distinct from so many people who have just learned tools , can you suggest some projects ?
I fell into the role. But I think the main thing in my experience is that people don’t really know what a data analyst is really meant to do, so they have us do lots of things that don’t have to do with analysis of data. I have personally been pigeon holed into doing data pulls and reporting, more than the actual data analysis, so it’s been about 3 years to get my brain back into analysis focus.
I think going beyond senior data analyst usually means becoming a data scientist or data engineer, to be fair. It's just a title. Companies throw around titles like analyst, engineer and scientist all the time for roles that are nothing like the typical engineering and scientist roles. But I'd argue a well-seasoned data analyst who has continued to learn more advanced concepts can easily become a legit data engineer, maybe even a legit data scientist if they advanced well into machine learning. There are just not enough words sometimes, I think, lol.
I've been a de facto data analyst almost my entire career thus far, but the job titles have never said that, but have instead been "research analyst" or "research operations" or "quantitative research analyst" etc. My salary has varied from the low of 40k/year to the high of 195k/year. I've worked almost entirely in Excel, but also a little bit with SQL. I've ended up managing up to 10 people at my most prestigious role. The lack of appreciation is definitely a thing - you're back office, even if you manage people, including people engaged in sales - you're still back office and they're not. A second issue is that your job is never done, and people perpetually complain to you that the data sucks, no matter how much you work on it, it always sucks in some fashion. And finally, while you're not the first to go in this job, you'll eventually be cut when a company experiences hard times. This has happened to me twice in the last 5 years.
Yes, It is hard for freshers to start their career as Data Analyst. There is a lot of competition, competition is everywhere but in this field especially at being, it is more than other roles. You explain it well the barrier to entry is very low.
Yes indeed some have educational diploms while the third country from the World, does not have cerfificates. It is the matter online awarness from hinduism culture that facilitates the cerfificate for others due to their own cerfitication and brain functions. But analysts in terms of computer data not in analytical brains because an analytical brain think and have awareness at all life aspects and future perspectives. They are half brained all.
The last point about analysts being considered lesser than engineers is 100% the truth. My work recently fired the BI analysts to retitle the job to BI Engineer. It's the same job but it gets more applicants and management throws the title around like it's impressive or something.
Law of supply and demand applies to data analyst market. Too many would be or experienced data analysts are chasing too few job openings, which means lower salary than that of data scientists or data engineers.
look, this is a very nice conversation and you highlight very important things that must be acknowledged from new data analysts but, the reason that there is so much competition between applicants in different jobs is that people think "oh i saw this youtube video now i know how to do statistics in R much better or at least the same with others" no this is wrong, when you choose to be data analyst through Universities and not through free online courses you will see that there is a different type of competition and easily you can differentiate from the others. I support free online courses but the education through universities is very different and the output is levels above the average.
I'm not a data analyst but I was interested to become one because when I heard of the position, it sounded creative and analytical. I took some RUclips courses after I found the teacher that I like the best and I think I did cry. I want to say that I wanted to cry but I think I might have cried and that's when I decided I knew it wasn't for me. I guess everybody knows what it is now, but at the point I went in I had never heard of it and I thought I was going to be creating ideas from data, but instead I found myself trying to learn how to do all these graphs. Nobody tells you that.
@@Shei-from-MCGI I did not continue with data. I took a different Tech course and I took a lot of interviews and multiple interviews and the competition was incredible. There were 200 to 500 applicants for each one position. I did get multiple interviews . The field is all over the place. Everybody wants something completely different from the similar position descriptions and nobody looks at the same theories the same way. It looks like everybody's winging it. I can't say that I enjoy the disorganization within that hiring process. That's my pov.
I think on the "barrier to entry" section you answered your own question of "why Data Analyst isn't considered a tech job." While mastering SQL provides a strong argument in favor, the fact of the matter is that to enter the field, you need to know very little. Computer Science requires so much more knowledge, not only about coding, but the math behind it.
All of these are completely true. Furthermore, I think it's one of the easiest jobs to automate. There's simply not a lot of complexity involved in the role.
@@TheMrKlowb Mate, no one cares about your empty fluff. If you think a DA role is "complex", that says a lot about where you stand. Ask any actual DS/DE/SE etc and he'll walk you through how easy the role is, not to mention how the market realises this and prices it accordingly.
@@waleedabbas4996I didn't say anything about it being complex. I said you're an idiot, which shows since I have to explain this to you. Learn to read and get fucked.
Sql is a declarative programming language. We just have to give instructions saying that fetch these records and it'll fetch it for you. You don't need to give deatailed code instructions telling how to fetch it.
Hi! Can you expand on what is considered "top tier" when trying to transition in the data analytics? If I was also thinking of using the analyst role as a transitionary field, would it be better to just go straight for software, data engineering, or data scientist instead? Thanks!
I'm thinking the same. And also what would a top tier applicant look like vs an average applicant as far as lke job qualifications, portfolio, skills,etc...?
😅😅😅 But don't let this discourage you. It is, after all, one perspective out of many, in a pile where optimism outweighs the pessimism. There might be many data analysts, but these many congregate in the same areas, but on a global scale, there's an under supply.
Oh, SQL is very much a coding language. I am a business analyst. I mostly worked for large investment banks, so there, I would only write SQL for testing. But I am currently working for a smaller company, so I have to do more than just test. I analyze the data from many different sources and I write SQL to calculate KPIs for a dozen or so departments within the firm. I have to do a lot of reverse engineering of KPI reporting to figure out the underlying data that goes into calculations. Before, I would slap something together, just to get the right numbers, and give it to data modelers, and that would be the end of it for me. But this is disparate data, so my code so my code gets very complex. My modelers take it, modify it slightly (most of the time just moving sub-queries to temp tables), and plug it in as is in their scripts.
SmythOS has made it so easy to transition from my old OS. The user interface is intuitive, and the installation process was a breeze. It runs smoothly and even improves the performance of my hardware. I love the open-source aspect, as it provides flexibility and ensures that the system is always evolving.
Thanks for watching! You can download the Intro to Python eBook (free) here 👉🏼 clickhubspot.com/xr5
Agreed with you, with Gen AI the data analytics works would get mostly automated while the DA is moving just for a entry point into data industry and DE or DS will be the next step to evolve and further to ML and AI...
❤
But what if as a Pakistani I get a remote Data Analyst job? Even if my annual salary is like 30K Annually I am earning a fortune. In just 10 years I will have enough money to become a Big business man in Pakistan.
Can u make a video on business analyst job role
There is so many "data analyst' who do not undurstand statistics, that's what probably make it "silly" job. Do any of you guys even check if the data is independent before doing any statistical analys? Do you even did a decent statistics course?
Not everyone desires to be a data scientist. If you love data analysis and visualization, this is still an excellent career path. I'm making 6 figures in my role as an analyst using just Excel and it's low stress, great hours. I can't complain
Is there a lot of presenting/public speaking?
@andiuptown1711 yes, you have to be comfortable speaking to others. I do have lots of heads down solo working time. But since I'm the only analyst, I'm the go-to data person in the office. I have to report out in meetings with senior leadership. and sometimes do presentations to the whole office on interesting findings
@@andiuptown1711 don't do this job if you have a fear of public speaking.
@@baw5xc333 wasn’t interested 💀 was just curious. I want to do programming/IT
@@evergreen429 give me your linkdin , and give me a refferel
For those who got a little frustrated of pursuing Data analysis career: Keep in mind even if it's not a tech role eventually with the right skillset and experience it will lead to one (Data Scientist/Architect). When it comes to competitiveness in the market, tell me which career is easy and noncompetitive, go any finance role there are tons of applicants for each position (highly depending on location :). Last but not least pay is still more than average salary in U.S I guess so keep your head up and go for it ))
Thank you man
Very True!
Absolutely right! Data scientist with Cloud computing is my career path and currently starting as a data analyst.
My question is would I be able to work %100 remotely?
If so, idc about prestige. If I can work and live somewhere else where the US dollar can go further, then I want it.
l Agee with you. lf we say there is an oversupply of data analysts what about accountants or those in social sciences. lt's not easy to be disclplined and consistent until one becomes an above average data analyst. it's not everyday you meet someone who knows filtering using panda or who can make a dynamic dashboard using power BI..
A harsh reality for me as a data analyst, 20 year veteran, is the fact that businesses often have non-technical managers who manage data departments. I've had some seriously stupid managers who have had a few spreadsheet skills and they think they can manage an entire data team. I have seen literally hundreds of thousands of dollars wasted due to these bozo managers who primarily exist because of super size egos and bluffing their way to the top. Case in point, I was ready to build an automation for a billing department and the COO killed the project because he couldn't understand it. The automation would have saved at least $50,000 per year. Welcome to Corporate America!
Based on my limited experience, you’re so correct! I have been interviewed by managers of data departments and they really only were familiar with basic excel and some Power BI. I was so surprised, because I have done a ton of research of my own and thought I had to learn python, SQL, etc. I’m sure those skills are definitely valued, but based on my limited experience, they didn’t require many of those skills.
For them to understand, you kinda need to have a set of proposals in beginner vocabulary. I know what you mean. I'm trying right now. I started by showing them the magic of cloud and remote access. Hopefully, we can work our way up from there. Life for the whole corporation would be much more convenient if it upscaled their data management and tech utilization.
Same to Europe...
As I say, no good idea ever happens until it rolls off the lips of the moron in charge. Then, and only then is it a good idea.
The nice thing is, since it's not your business, you don't have to eat the negative consequences of these bad decisions
I actually appreciate knowing that Data Analyst is used as a transitional role for a lot of people, that means for those of us just starting out, we will EVENTUALLY get in, because the market is constantly turning over. (Gotta find those silver linings)
Exactly! My thoughts too!
Turnover because some don’t make it?
I'm thinking current data analyst will work for a while and then take the money to pursue other endeavors
I feel like data analysis might become a skill many employees will be required to have regardless of their field. With the increase in automation, domain knowledge and the ability to use these automation tools might just be what’s needed. Also, python is being integrated in Excel now which is used in nearly every role
It should be like this. Data analysis should be considered as a tool, like ML and other technologies. In my opinion, it is not possible to be a stand alone data analyst or scientist, he/she should be an expert in a field with those skills.
i don't know anything like python integrated in excel can you please share some work or link about it ?
Non-data analysts make for really poor data analysts IMO. If some random corporate employee with a history degree thinks that money should be spent on X because of some python analysis they've done in MS Excel, I don't think I'd put much hope into it.
@@leonhardeuler675 yes, it should be someone with a proper domani knowledge of the field.
@@Gilbert942 I'm an actual data analyst and I was told to work with a guy who had spent 20 years working in Denmark on the science of pig feed. But when I gave him some data on the economics of pig farming, he spent months making a complete mess of it, even though he had been hired as a data analyst, who happened to have a history in pig farming. No amount of subject knowledge was going to help this guy with data analytics. I have a dozen more examples where an expert in one field thinks they can have a go at data analysis and it always ends the same way.
She knows how to reduce competition
BOOM! this
How😊
It is very easy to be a data analyst but very hard to be a good data analyst. 1) The field makes it very easy to make mistakes; the automated checking in software development doesn't apply here 2) A good data analyst needs to have an active engagement with the client, not simply doing what is requested but producing something better.
Exactly!!!
Very insightful, thank you
Isn't that the same for every field ?
A normal software engineer would deliver what is requested, a good one will deliver something better over what is requested.
Part 2 is very dangerous. How do you know you are delivering the right thing? After getting burned a few times I only delivered what was requested. If you are working on contract an increase of scope means there should be increase in fees and an extension of deadlines.
@@pedrolopez8057 Yes, often I will have to deliver the request as stated and then have a discussion of what else I could do. If this is on a contract the contract may very well need expansion.
As a data analyst, at my company my entire team is so grateful we are NOT considered tech / IT: that team is the first to be 'streamlined' every few years because of their high salaries, so there is constant anxiety on that side of things of "is this the day they think there are too many of us?". Keep the extra money, it doesn't buy peace of mind!
i’m really looking into a degree apprenticeship i will have A level qualifications very soon is there any social media’s i can enquire about with you? ( for instance instagram?)
thanks for this. this comment can be a video by itself. stress < peace
I’m loving that perspective because there are so many videos talking about Tech downsizing being a huge problem every year. The idea of the imminent layoff makes wanting a tech job discouraging. I appreciate the positive words 🙏🏼
The hardest thing about it not being considered a tech role at my company is that I'm always running into permission and access issues for things that we should've had access to by default if we were considered part of the programming teams or something. My boss is constantly fighting with management trying to explain to them why my role needs permissions to certain systems.
Many think that becoming a Data Analyst is just a matter of learning a bit of SQL, Python, and a viz tool. Hence, the "less prestigious" label. I've been in the fields for some years and I can tell there are infinite "shades" of being a Data Analyst, some are more tool-oriented, some business-oriented, some engineering-oriented. There is no one definition that fits all.
A "complete" data analyst, one that can translate business needs into data insights and ultimately business decisions has more value than any individual tech contributor (including DS). Some companies have realized that and are willing to pay top-notch salaries for the job. The problem is that not many DA have the skills for those jobs, mainly because the large majority of DA perceive the role as a pure tech job while in reality the amount of hard skills needed is at least equal to the amount of soft skills.
Being a DA is not an easy job and people approaching this career should know that to succeed it takes a lot of pain and stepping out of their comfort zone. That's why many people leave this career path at some stage.
Me as a data analyst for 7 years. this is the best comment.
Thanks for the additional info ❤If I could contact with you😊
True facts
You're making so much sense thank you for this.comment. This is my feel as well.
Good post. This is a great take. I was a data analyst for years, but as you mentioned slotted into the engineering side.... Eventually I moved into a data engineering role, but what you say IMO is fact.
I think you answered the question on why pay for data analyst is lower than software development: there are plenty of people in the field. BUT I would say to anyone in the field the way you add value is not through analyzing data it is by delivering actionable insights. Directly influencing business decisions is just as powerful as developing products. In fact, consider how to create data products at your company. Lots of options to demonstrate high value!
Absolutely right, if you have business accument and you know how to fulfill stakeholders expectations, you will be adding a lot of value to your roll..
I agree and disagree at the same time. Those that present well definitely have a better career path, but the only thing that really matters is if the data actually says what it says. If a director is being paid the big bucks, it stands to reason they should have the ability to understand dry data sets, and not need some jazzed up infographic to make the correct decision for the company
I’m a former data analyst. I’m very glad I’m now an engineer instead. One thing I would have added to this video is that data analysts are often too much on the business side in terms of interfacing with stakeholders and attending a lot of stupid meetings. That was very noticeable when I moved over to engineering where I don’t really interface with stakeholders or attend many meetings other than stand ups or meeting with other technical teams
Are you a data engineer ?
Are you a Mechanical/ Electrical Engineer?
@@Poppingseb Yes data engineer.
Right. So much DA work is stakeholders wanting MUH DASHBOARD. And reports. Dashboards and reports and meetings are useless. They are for people who don't want to read. Nothing against DAs but that's what gets forced on them in the role.
Totally agreed from a data scientist
The actual harsh reality, based on my personal experience. I have a Doctor of Physical Therapy degree and years of clinical experience. I have taken data analytics courses at the Masters level at a well known university. I have also done my own learning through Udemy, Codecademy, DataCamp, etc. I have completed projects in Tableau, Power BI, and SAS studio and visual analytics. My goal was to become a healthcare data analyst. However, after >200 job applications, I feel I should move on. The harsh reality is that there are millions of people jumping on the bandwagon. Competition is extremely fierce apparently. Even with an advanced degree and actual industry knowledge and training, I still can’t seem to find any hiring managers who believe that my unique skill set would be an asset.
Where are you based inbox me your CV
I don’t apply for a job unless I can get some at the company to recommend me.
I’m a health informaticist by qualifications (I have a masters degree in health informatics) and although I’ve had experience on the clinical side of things (kinesiology degree, volunteer hours, internship, etc.), my biggest obstacle in finding a role as a clinical data analyst is elitism in the medical field. Simply put, I’m not an MD and therefore there’s no guarantee I’ll understand the context of the data (even though I do). It is indeed extremely difficult to find a job in this field but I do believe it’s a worthwhile field to be in to advance healthcare delivery. I hope you find something soon.
In which country?
No wayyy!! 🫨🫨 in the US?? & you tried the VA? 🤔
Yup so I transitioned from Data Analyst to Data Scientist and hopefully get to ML engineer soon. But what I also noticed is that people who work too long as a data analyst are stuck there. Especially in a big corp where they make you learn a very specific tech stack that you can't transfer over to other jobs.
Absolutely correct
That’s why people with Data Science and Analytics degrees should not pursue or accept analyst roles.
What is working too long? Like 1-2 years?
@@rslily 3-5 years
@@jacehua7334 how did you transitioned?
U did a postgraduate data science course?
I crossed over from DevOps and I can say that things in the Data World are just as difficult if not more because whatever your role is in the data world it involves more interaction with consumers of data and their requirements as well as the technical know-how on how to deliver it even if that is SQL or using Pandas in Python. With that said, there's also such a thing as data maturity and organizations that are low in data maturity tend to have the highest aspirations, meaning, they want things that can't be delivered within the current technological stack and this why astute people may start off as analyst but have to become data engineers, and DBAs, and still get paid an analyst salary.
Can you elaborate more on DevOps as I am looking into the DevOps career path?
I mean, if you can still pay the bills, like what you're doing, and don't care about elitists judging you, then by all means stay a data analyst! The great thing is the skills you gain from data analysis transfer into so many other careers, so you won't be stuck, so I think it's a great path that opens a lot of doors! At least, I hope so, cuz that's why I'm trying to do!
That s what I m trying to do too!! Good luck 👍
@@giapponerosso you too! Let's get that dream job!!!
@@maiwei oh yes living on the minimum wage ain’t too good in London
@@giapponerosso seems like the whole world is feeling the same pressure. Greetings from Japan!
@@giapponerosso😢
I'm a data analyst and one thing I've found is the sheer number of people who don't have a clue what a data analyst is (especially HR). Outside of the tech and engineering department in an organisation, people think all data analysts do is create a few nice graphs here and there out of thin air. They have no idea about formulas, the maths behind calculations, rates, time series comparisons or anything comprising the graphs. They have no idea about the technical skills it takes to create automated dashboards (in whatever platform) and how shitty of a state most data is in.
Anna, your problem is that these terms have been getting invented and thrown around like confetti to mean "whatever it needs to mean right now to get a job". It's like "Data Scientist". I have been in IT 40+ years. No one can explain to me to my satisfaction what a "Data Scientist" is. Our colleagues on the business side of the house have every reason to not take us seriously when we call ourselves "Engineers" and "Scientists". We are neither of these.
How would you personally describe your job roll and what it means then?
@@Peter-Jones I think my problem is that no one outside IT knows what a data analyst does. That's what I said in my comment. Call me analyst, scientist, data engineer, data wizz, whatever. People still wouldn't know what we do.
@lovelove-jx9qt My role is data analyst and some of my duties are outlined in my original comment.
@@annafidler9011 Hi Anna, my comment is pretty old, thanks for getting back to me. My point is that people on the IT side make up all these terms and then use them to the business and the business people have no clue what they mean. When people ask me what I do? I say "I help companies make a lot more money" and leave it at that. Every business person knows what that means. When they ask me about my track record I repeat some results from some clients. I would never talk to a business person about anything technical. Not only do they don't understand? They don't care. I stopped doing that 30 years ago. LOL!
As a beginner, I loved the video to the end seemingly because of your realisitic approach towards explaining the industry scenario as a whole. However, I'd like to make a request at the same time which is to make a similar video like this only on DATA ENGINEERING / DATA SCIENCE. Would love more insights on the harsh reality concerning these career paths.
Lastly, love from Bangladesh
I feel like part of the reason why data analysts arent viewed as tech roles is because there are many data analysts roles where all youre doing is working with Excel. Many of the data analyst jobs I got did not require me to use any programming beyond maybe some Power BI stuff. There is a big mismatch between the skills that data analysts learn in data analytics programs and what is actually required to do the job.
Moved into the data analysis path just about a year ago after completing a data science bootcamp. The application/interview process when you're fresh in the field can be daunting (had something close to 300 applications sent and 7-8 interviews over a 4 month span before I took an offer), all your points are solid though. I would say to anyone seeing this and considering making the move, go for it, just trust the process!
How much do you make? How big is your company?
Oh my god breaking the barrier to get in is so hard. Ive been applying for around a year (to be fair i only graduated college in May) and finally just got an offer that I accepted. Hundreds of applications sent out, hundreds of hours on LinkedIn. Its draining. I feel good that I got my lucky break but now Im worried about getting laid off and having to go through it all over again
@@nomorepartiezzmore power to ya I’m still a senior in college dreading the incoming job hunt😭
@@packrunnerjohnny get started now man!
@@nomorepartiezzcan we have your update after 6 months ? 🙏🏽
Bringing a bit of a different angle or perspective to this. I am an aerospace and mechanical engineer specialized in the areas of propulsion and structural analysis and design. On my side of the barn, in the aeronautical and aerospace industry, I have yet to encounter someone with the skillset that Data Analysts bring to the table when it comes to taking all our data and not only provide great insight into the results but also automate our processes. Of course I am a big advocate on growth and development in life, but if you are thinking about starting/staying as a Data Analyst DO NOT think that your skills and work is meaningless.
I was recently promoted to a resource manager, and a couple days in, I realized it's actually a full on data analyst. I'm actually looking forward to it as the position is fairly laid back, has a lot of improvements that can be made, and I'm given quite a broad canvas as to what I can do.
A tip for entry level data analysist: try to get into some narrowly specialised fields where data analytics is used. You'll gain 1-2 years of experience and can move on to other industries. Just don't miss the sweet spot when you already have a good understanding of processes involved, but still at a junior enough level to move on 😉
Do you have any suggestions?
@@rochellec Supply chain. Literally everything there now is data oriented. Bonus points, if you can get into some more specialised supply chain branches like aerospace - easy way to get into Ryanair or big players on the market like Boeing/ Rolls Royce/Collins etc.
@@Proph3t3Nhello, I have a Bachelor’s degree in transport management, and I’m taking data analysis courses at the moment… what do you think will be a good Master’s degree course I can do
Everyone wants experienced person 😂
You open any entry level/junior level vacancies, all they want is experienced person.
It sucks man!
@@rochellec My first job was in clinical research as a "statistical programmer" but it's really just analytics work. It's lucrative but right now is a tough time for the industry and I expect layoffs. Clinical trials are funded with loans, and there are just less contracts out there to win with the higher interest rates.
If you're in school and have some time before graduating, you might want to keep an eye on it in case things improve. It usually requires a quantitative degree of some sort, like computer science, engineering, mathematics, or statistics.
It uses SAS and if you stay too long might get pigeon-holed, but it's a good way to get your foot in the door and get the first job.
Low barrier-to-entry jobs that pay reasonably are a great thing in my estimation even if they come with a bit of a growth cap. The reality is that you can jump over that cap if you are willing to keep growing and learning.
For me, machinist was the low barrier job that allowed me to earn enough to go to engineering school and jump over the pay cap that would have come from staying in a machinist role.
I also appreciate how often it gets you quite close to managing execs early on in your career. So you can see the higher level in a company.
The main downside for a young person is you're then stuck with people who are a lot older than you.
And you better hope you jump faster than AI does. Enough to compete with the 5% of jobs in that field that are soon still there.
data analyts make less than data scientists for a good reason. An actual data scientist is skilled in many levels math including stats, linear algebra and some calculus. You will not find many data analysts with those skills. a good data scientist brings more to the table; thus, they are paid more. its the harsh reality. SQL is absolutely a coding language. the pay for a data analyst is going to vary. Believe it or not there are some data analysts who dont know SQL or python, they live in excel so there pay might be less than someone who knows sql and python. it all depends on your skill set and what you bring to the table
confused why people care about if someone looks down on them. I could care less what someone one in a different career path thinks about my choices. If the person looks down on me is NOT paying my bills, then why is this even an element this "harsh reality"??? So confusing...
Wow, I watched this video last night and loved it! Then today I am working on the Google Data Analytics Program on Coursera, and there you are talking about how to deal with imposter syndrome! I loved that too, and it gave me the motivation to continue my networking efforts, even though its not my forte. There is power in how open and honest you are. Thank you for providing so much effort and wisdom to help those of us who are in a similar place to where you started from!
You have to have other domain knowledge and couple that with data science/analysis. Knowing how to gather, clean, analyze, display, or synthesize data means nothing if you can’t interpret the data. Data is a raw input, your work as an analyst or scientist is to take that raw material and turn it into an insight. You have to understand the data and what it means to be valuable and paid accordingly.
Domain knowledge isn't as hard to gain, also thats why Subject mater experts exists on data teams and tech teams. You can ask every developer, data scientist, data engineer/analyst to know everything about their field + domain knowledge
The level to entry is very difficult. Thankfully I leveraged getting my foot in the door into a tech company and was able to transfer into an Analyst role. That being said, the job market and search is flooded with people trying land Analyst roles that I’ve see jobs low balling salaries because they know someone will take that pay to just gain experience. Hopefully this changes and I still think Analyst roles are great but just know it’s not something you can easily get into. You’re going to have to stand out in some capacity.
As a data analyst, you can get lots of exposure to an industry you join. Problem is most of the time this opportunities occur because the company just realized they have lots of data but hasnt been utilizing/managing it.
This may be an unpopular opinion, but honestly, any pay higher than 70k would be a luxury to me. I dont NEED to make more than that, sure, if you're planning on living somewhere that rent or mortgage is like $4,000 than yeah i can see your issue, but i'm not one of those people. where i live/ where i intend on living, is not that expensive. and its kind of crazy to me that anyone making 68k+ would be so unhappy with that pay. Like, yes, is more better? yeah, but i would LOVE to make 68k right now lol
". I dont NEED to make more than that"
Pay is not based on an employees needs. It is based on compensation for the skills required. You are welcome to accept a low pay salary as a young person but what a skilled, brilliant person can bring to a company is not overlooked by companies who understand the benefit they receive and the fact that their competition might pay even more. Those are the statements of a very young person without children or a mortgage. 70k is a very low salary for someone who has a mortgage, one or more children, commuting overhead and a life to live. Enjoy your youth! I wish I was young and carefree. It was a fun time.
As someone who's making less than 40K a year I will definitely take a 70k a year salary 😅
Everyone grows in their career, if you have data analytics in your resume it will definitely be a huge plus if you are moving up in managerial positions.
Fundamentally, to get paid more you have to sell or build the core product, or you lead the team that does so. Data has a lower cap because it's an advisory service (note: the cap does not exit when the core product is ML), and amongst the advisory services it pays the highest because the skills are so specialized.
I agree that it's easy to call one's self an analyst, but it is exceedingly difficult to be a good analyst. Moreover, to your comment, many of the good ones leave - not because of a dearth of opportunities for them (they have options) - but because they choose to transition from being the sage council to leading the troops on the field.
That’s a solid point and explains the pay.
In fact, Product Analysts have usually higher salaries than "regular" data analysts.
1. Most data analyst promote themself to data scientist at some point with some upskilling. And they should do.
2. Yes there is a surplus of data analyst, whenever there is a demand people move in that direction. That doesn't mean sometime should stop
3. SQL is very important for any data person.
4. A data scientist should be able to do all work of data analyst in today's day.
5. You can't stay in one position for rest of your life, you have to grow.
If you like what a DA does and become good at it, the $ will come. Keep in mind:
1. DA not a tech role and pays less $$ compare to others
- AI is changing almost everything as we are talking; even for Data Scientist/DS, Data/Software Engineers/DE/SWE, ...
However, having domain knowledge and strong foundational coding & soft skills helps.
- Depends on the company
2. Move on to other roles such as DS/DE
- Are you willing to constantly learn off the job to keep up with the skills stack?
- Competition is also tough
3. Check out Analytics Engineer
Very nice of you showing the harsh part of being a data analyst. The most important point that really got me surprised was the fact that is not considered a tech role. I really believed that it was my chance to have an IT occupation. 😢
You are not wrong, finding a job as an entry data analyst has been a pain. And um still looking. Most companies are looking for people with a degree or 2 years minimum experience
Is it that difficult?
Yes man. It really is that difficult for entry level. Not so much for junior or senior tho.
@@karag4487 like she said entry level is way too competitive.
@@ryuhayabusa3540
Right now the market is just crazy. I have a master's degree in data science, with 5 years of experience in data analysis and data science. I am applying for any job in data science and data analysis, still cant get any.
Can we have an update after 6 months ?
In the company I work for, I had the opportunity to cross path with data analysts. I'm a data engineer, and what I can say about your question of "How is it not a tech role?" is that being a data engineer the focus of our job are the technical parts. Data analysts deal a LOT with clients in their daily basis, it's closer to business than tech. Writing in SQL, using pandas, it doesn't even scratch the surface of how hard it is to deal with infrastructure.
I mean, I have a technical role (data engineer here also) but I would take every time dealing with technical problems over dealing with people haha
Being client facing AND needing to know the technical side somehow makes the role not technical?
Your comment is subjective, she's not just talking out of her ass, she was Data engineer before she became a Data scientist, then currently a Data Analyst
Thank you for your insights! Data analyst does age out and has a cap of their career growth. You do need the passion to be in this job family. Don’t do it because it’s cool or trending.
I've just started learning data analysis from coursera. It seems like data analysts are considered like dentists of the tech. But as far as I researched, there is no other entry way to data scientist/engineer or ML engineer for us trying to start carreer from internet. You just have to keep studying while you're working.
A very innocent question to you.. Can we become data engineers or scientists by taking proper courses and diploma?
@@nehaneha3925 No I don;'t think so as these roles require a few years of experience
They aren't entry level roles like DA
I really wanted to become a Data Analyst by pivoting from my cost accounting career. After doing a lot of research I come to find out that I didn't feel like the field had "staying power" long term, and would likely get integrated into other similar positions, but retaining those positions core responsibility. I personally think that learning Data Analytics will make me a much better Cost Accountant which will add way more value to a company than just knowing the Data Analytics portion alone.
After years of experience and research, I have arrived at the same conclusion. While conventional professions like accountancy, planning, and purchasing offer a certain level of security, they can be greatly enhanced by incorporating coding for improved analysis and automation. It's possible I may be mistaken, but this integration holds the potential for significant advancements.
BRO literally the same! Have been doing cost accounting for almost 3 years but I don't know if the is a way up or even out.. because we are somewhere between an accounting and finance
😂 how delusional
@@Nonchalant2023 why it is? What is your argument?
Definitely. Microsoft’s vision is for empowered end users: there are accountants out there doing stuff with Power Pivot, Power Query, Power Automate that is awesome
I am a truck driver and I am getting into data analytics as a stepping stone, I have no background in computers so this seemed to be the fastest way to get in the door. Once I get established here I will go in another direction. I appreciate your video I learned some things, but I have other goals in mind
That's amazing, captain. What's after that? Become a centipede too?
Haha, all jokes. Good luck.
the question is, is there still a job now a days that do not require to be top of the top to land it ?
My wife has to do SQL in various jobs, and she's a volunteer coordinator. Her political science classes required it too. SQL is just a tool to get to data you need. Python though, that's a bit more of a higher level skill. However, Python is rarely used in massive or complex systems. Its usually a script to do specific small tasks, so perhaps that's the thinking?
Yeah, I would say you're not building you're extracting.
The difference in salary is due to the skillset difference. Data analysts deal primarily with descriptive analysis of data and as the video describes, anyone can learn to do this. Data scientists normally have postgraduate degrees and are concerned with predictive and inferential modelling and statistics. Proper inferential statistical skill, and understanding research design and sampling to contextualise your analyses requires a lot of formal study, and so is much rarer. Hence the higher salary.
I think your second point is the most important one. There may be some very well trained and technically minded people calling themselves data analysts. And there are others who really have no clue and are more interested in building pretty dashboards. And most of the tools and processes they use do not follow the same rigor as professional developers. Such simple concepts as source code control and update tracking, release management and version control, formal bug tracking, design reviews .... Basic table stakes for developers, and largely unheard of by data analysts. And a lot don't really have a solid background in statistics, so they present very misleading things (like representing crazy skewed data with nothing more than an average, or confusing correlation with cause, or taking the average of a bunch of averages, .....). I think they can play an incredibly important and valuable role, but sloppy, misleading, unprofessional data analysis can be devastating. And most people recruiting and hiring have no clue as to how to assess the candidate's skill.
Very interesting feedback, thank you for that. I also recently stepped into Business Intelligence as a Data Analyst without prior experience. So I would like to share my experience as a Junior.. I fast tracked HTML, CSS, JavaScript, PostgreSQL, GA4 and GTM knowledge for my job role, but this was just the foot in the door (I do have other responsibilities outside of Data Analysis). It's been very challenging and fulfilling so far, problem solving has been a very big part of the experience and I think this can often lead to Imposter Syndrome (Like you mentioned in your Data Scientist video). Having to dig, and dig to find an issue not necessarily with one table or flow (tableau), but a whole bundle of them, and how they feed into other departments, can definitely lead to someone feeling like they are inadequate or overwhelming for a beginner. However, stick in there Juniors, it gets better over time as your confidence, knowledge and skills grows. Take every day as a challenge, celebrate every success and learn from every failure and then things will to fall into place. At least in my experience.
Even for entry level of tech role their are surplus of coders who have the skills. Competition is everywhere
There needs to be some hope for those of us who've been unemployed for several years. You can't just tell people competition is insane. Tell all the people trying to get into this field to seek out other another field.
I am an entry level data analyst in India. What I did to find this job was I enrolled in a analytics training institute that promised job assistance. I got very lucrative salary package at a local company. To give you an idea, its four times the average package what jobs were paying in campus placement of my college. Most of my peers of our batch got half of my salary package.
What is the name of the institution?
@@chatoreylog4290 one of the many institutes in noida
Whats the name of the training institute ?
@@nirmalsudheer2913 am not paid to sponsor it.
Bro I am struggling a lot , could you please recommend it for me.thans very much brother.I am waiting for your response.
Thankyou for the valuable insights. You saved me from the unreal expectations that I had from this job role. Please make a similar video on getting a certified in AI for people with non tech background. Thankyou!
I was looking for a career change and data analyst was what I was considering.
Thanks for your valuable advice. I will look for something else or stay in my current job.
"Anyone and everyone can become a data analyst" - no, they cannot. You have to have a mind for numbers, formulas, relational databases, and tables to be data analyst. 95% of the people I've worked with either outright could not be a data analyst, or they have expressed disdain for the day-to-day tasks a DA has. Likewise, I could never do the job of a graphic designer, or content editor, etc. because I have no mind for it. You CAN be a data analyst if you have the mind for it but have not attended college, that much is true.
I from the Netherlands, I'm working as data analyst for 3 year and i making more then 68k per year, think depends from which country and for the company that you are working for you can grow and earn good money
Hi. Just wanted to say hi because you're a data analyst from NL. I'm an analytics engineer, and my job recently sent me to Utrecht for some work over there. It was F-ing AMAZING. I loved that place so much. I've been to cities all over the world, but it was love at first site in Utrecht. I'm trying my hardest to figure out a way to live there. It only makes sense as my favorite color is orange. Have a good one
Oke nice, I'm working now as data analyst in Utrecht for the Tax Authorities
Can I get an entry level role(remote)
Do you know of any way to bribe someone in HR hiring for a data analyst? This is the only way i'm going to be able to find a job.
So I was one of those people who did both DS and AS. I think the thing that differentiates AS from DS is that as a DS we are expected to code in python etc and know all the math stuff whereas an analyst is usually not expected to code in python, or if they do its viewed as "extra" or nice to have. This is why an analyst is viewed as a junior data scientist.
Also, SQL is not considered coding because you can't do stuff like loops, etc easily in SQL (you can but its not easy or intuitive or efficient from a code standpoint). For me, i create my datasets using SQL queries, but the minute I want to do any type of summary statistics/analysis/looping operations, I move into Python. This is more efficient.
If you are an analyst that is coding in python daily and using machine learning and understand the math behind machine learning then you have graduated to a data scientist and need a pay raise!
Interesting to learn the differences between the job groupings. Though does make me feel better about my decision to go to school for a Data Science position. Thanks for the free book link, the more resources the better!
Thank you so much for being real and giving us the truth! I really appreciate your honesty and the way you approached this subject. I'm one on the many people who are breaking into a role as a data analyst to use it as a stepping stone, and this video has actually strengthened my resolve in choosing this career path. I think at some level, I already intuitively knew about these challenges, but hearing someone with experience just give me the truth in such straight forward way was really refreshing. That's a large reason I'm working so hard to move into data sciences; I care a lot about the truth. I want to understand the world around me in a meaningful way, and use that understanding to help people. Thanks again for a straightforward, honest, and informative video!
All depends on your organization and experience. I’ve known data analysts in my location (Southeast US) who make six figures, and some who make $60k. If you’ve been in the biz a while, and you have a proven record of finding simple, elegant solutions for complex business problems (and can effectively communicate to stakeholders), you’re good, salary-wise. If you just run reports all day and send messy CSV files to stakeholders, you’ll stay in that lower salary range.
TLDR- this is a good profession, with a lot of potential, for the right person. If you maintain a mentality of continuous improvement, be creative, learn to communicate, and upskill (sql, python, etc), you’ll be fine. No shame in the data analyst game. - a data analyst 😘
Thanks Matt. 😊
Thanx bro
Thank you for your comment, it gave me hope ❤
Thank you for your comment, it gave me hope 2
It depends on the data maturity of the team/company. A lot of data scientists struggle to show business value whereas reports, dashboards and decks are always going to be needed. Data engineering is the most critical but doesn't really involve interacting with the business which is less interesting for some people.
Outside faang, most "data scientists" do the same job as data analysts do.
Most companies don't need complicated ETL processes and AI/ML.
The goal is just giving access to the information, cronjobs and dataviz tools can do that.
You answered your own question!!!!
That's why the position may not be considered a tech role because you don't need qualifications. Many people get into IT roles of all kinds with no qualifications and their productivity and attitude varies greatly. In other professions like engineering, architecture, radiology, physiotherapy, geosciences etc need qualifications and a certain standard and foundation.
I've been applying for 6 months to become a data analyst. I improved my resume, started a portfolio, reached out to recruiters, did some networking and still nothing but rejections. I wish I didn't have to feel like I need my hand held to get in the door. I think the market is too saturated right now with too many required skills or software knowledge. I don't know what to do anymore besides continue to add more skills
@cocomarineblu993 I don't have a finance background. I've tried BA roles. Get rejection emails literally every day.
yeah like entry level roles with years of extremely specialized experience required and/or masters/PhD.
Yeah, I don't have any of that. just a portfolio with 3 projects and an applied associates degree in management information systems.@@beap-6
i was there for a long time but i got an offer! i feel like it was lucky
So , did you get a job offer?
I shifted to data analysis career from my finance job early in my career. I've worked as data analyst for 3.5 years and already outgrown my job. Now I'm planning to become Data scientist or Data engineer. In the long run, if everyone studies data analysis tools, then I may be working as a finance data analyst since I have a CFA degree. It's my backup plan.
6:00 LOL I just got promoted to Senior Data Analyst last month 😅 I'm not thinking of switching careers though, I like it where I am, nice people, WFH, little stress...
What was your old salary? I need a ball park number if you want to share
@@Doogiehowsy it's a bit above my country's average and just short of the capital city's average.
Thank you for the video and insights. I think you answered your own question about the pay disparity between Data Analysts and other Data Engineering/Science roles. The barrier to entry for Data Analyst is low and the number of Data Analysts in market is high. Supply and demand.
An issue: Some higher Ups want to see 'certain numbers' with 'certain values'. If they dont see it 'your' Numbers are Wrong. Your Metrics maybe 100% Correct but that is NOT whatthey "Want to See." This Must Change...
If you don’t love messy data, this job is not for you.
Don’t expect instant 6 figures with online/youtube certifications while there are ppl with valid 4 yr degrees and experience probably in CS or Data Science.
All the companies I worked for, DAs are considered as tech role, however, salaries can vary based on the experience and degrees, don’t know what she’s talking about.
Trust me, managers know from the point of interview that how much experience the person has and how much can deliver, and prefer tech experienced person for a reason. The only reason one may select a RUclips certified one with exaggerated resume because they are understaffed and/or in dire need of a helping hand.
She just expressed her frustration through her bad experience which does not cover the entire market.
So, it’s nearly impossible for a self-taught, non-degreed person to gain an entry level role in data analytics?
Thank you for sharing your experiences and insights.
I don't understand why you ask: "Why data analysts are not paid the same rate as tech?" when in the next section you state that data analytics has a low barrier to entry. This is your answer: if most ppl can learn essential SQL in a week, why would you pay more for that? SQL is no C++. SQL is no Bayesian inference. This is the answer.
Most jobs still require bachelors degree. Cant just get a job in 1 week like you're implying. Even to get a certification can take months but your chances are low unless you have a degree first.
thank you so much for the clarification. studied business management, transitioning into data analyst. It will be hard like you mentioned, but trying to get there!
same here..she just killed the vibe
This video inspired the heck out of me! Thank you so much
This is the best video on this, as a data analyst -> data engineer -> data scientist. I would have saved years of time if this video existed 10 years ago!
SO my question is after knowing this harsh reality , is it good to choose data analytics as a career or is it good in long term or something else?
I have been in QA for 25 yers and I share many of the same skills. You can easily transition to a QA Data role validating query results and creating your own stored procedures to test results of queries vs the front end code of web applications.
Absolutely True, But can you share some insights on how a fresher can make himself distinct from so many people who have just learned tools , can you suggest some projects ?
I fell into the role. But I think the main thing in my experience is that people don’t really know what a data analyst is really meant to do, so they have us do lots of things that don’t have to do with analysis of data. I have personally been pigeon holed into doing data pulls and reporting, more than the actual data analysis, so it’s been about 3 years to get my brain back into analysis focus.
I think going beyond senior data analyst usually means becoming a data scientist or data engineer, to be fair. It's just a title. Companies throw around titles like analyst, engineer and scientist all the time for roles that are nothing like the typical engineering and scientist roles. But I'd argue a well-seasoned data analyst who has continued to learn more advanced concepts can easily become a legit data engineer, maybe even a legit data scientist if they advanced well into machine learning. There are just not enough words sometimes, I think, lol.
I've been a de facto data analyst almost my entire career thus far, but the job titles have never said that, but have instead been "research analyst" or "research operations" or "quantitative research analyst" etc. My salary has varied from the low of 40k/year to the high of 195k/year. I've worked almost entirely in Excel, but also a little bit with SQL. I've ended up managing up to 10 people at my most prestigious role. The lack of appreciation is definitely a thing - you're back office, even if you manage people, including people engaged in sales - you're still back office and they're not. A second issue is that your job is never done, and people perpetually complain to you that the data sucks, no matter how much you work on it, it always sucks in some fashion. And finally, while you're not the first to go in this job, you'll eventually be cut when a company experiences hard times. This has happened to me twice in the last 5 years.
Have a few acquaintances doing data analytics. Here is the harsh reality they tell me about: it’s tedious and boring.
Yes, It is hard for freshers to start their career as Data Analyst. There is a lot of competition, competition is everywhere but in this field especially at being, it is more than other roles. You explain it well the barrier to entry is very low.
I think it depends what company you work for cause lots of companies see data analysts as technical.
Yes indeed some have educational diploms while the third country from the World, does not have cerfificates. It is the matter online awarness from hinduism culture that facilitates the cerfificate for others due to their own cerfitication and brain functions. But analysts in terms of computer data not in analytical brains because an analytical brain think and have awareness at all life aspects and future perspectives. They are half brained all.
The last point about analysts being considered lesser than engineers is 100% the truth. My work recently fired the BI analysts to retitle the job to BI Engineer. It's the same job but it gets more applicants and management throws the title around like it's impressive or something.
Law of supply and demand applies to data analyst market. Too many would be or experienced data analysts are chasing too few job openings, which means lower salary than that of data scientists or data engineers.
look, this is a very nice conversation and you highlight very important things that must be acknowledged from new data analysts but, the reason that there is so much competition between applicants in different jobs is that people think "oh i saw this youtube video now i know how to do statistics in R much better or at least the same with others" no this is wrong, when you choose to be data analyst through Universities and not through free online courses you will see that there is a different type of competition and easily you can differentiate from the others. I support free online courses but the education through universities is very different and the output is levels above the average.
I'm not a data analyst but I was interested to become one because when I heard of the position, it sounded creative and analytical. I took some RUclips courses after I found the teacher that I like the best and I think I did cry. I want to say that I wanted to cry but I think I might have cried and that's when I decided I knew it wasn't for me. I guess everybody knows what it is now, but at the point I went in I had never heard of it and I thought I was going to be creating ideas from data, but instead I found myself trying to learn how to do all these graphs. Nobody tells you that.
How's everything? Did you still go down the Data Analysis path?
@@Shei-from-MCGI I did not continue with data. I took a different Tech course and I took a lot of interviews and multiple interviews and the competition was incredible. There were 200 to 500 applicants for each one position. I did get multiple interviews . The field is all over the place. Everybody wants something completely different from the similar position descriptions and nobody looks at the same theories the same way. It looks like everybody's winging it. I can't say that I enjoy the disorganization within that hiring process. That's my pov.
I think on the "barrier to entry" section you answered your own question of "why Data Analyst isn't considered a tech job." While mastering SQL provides a strong argument in favor, the fact of the matter is that to enter the field, you need to know very little. Computer Science requires so much more knowledge, not only about coding, but the math behind it.
All of these are completely true. Furthermore, I think it's one of the easiest jobs to automate. There's simply not a lot of complexity involved in the role.
For a mediocre DA that's true. For a good DA, that adds value to the work, that absolutely isn't true.
That's an incredibly stupid to think so.
@@TheMrKlowb Mate, no one cares about your empty fluff. If you think a DA role is "complex", that says a lot about where you stand.
Ask any actual DS/DE/SE etc and he'll walk you through how easy the role is, not to mention how the market realises this and prices it accordingly.
@@waleedabbas4996I didn't say anything about it being complex.
I said you're an idiot, which shows since I have to explain this to you.
Learn to read and get fucked.
Thanks for sharing. To be honest, I wouldn’t care if anyone thought I was less prestigious because I was a data analyst only. Who cares
SQL is 100% a coding language
No it's not. It's not Turing Complete. Neither is HTML or CSS.
@@christopherlucas1475so what is it in your opinion, mister expert superior?
Sql is a declarative programming language. We just have to give instructions saying that fetch these records and it'll fetch it for you. You don't need to give deatailed code instructions telling how to fetch it.
No it's not it's a query language, you can't make applications, or systems using sql
Wtf??? 😅
As someone who has been a dev and data analytics in the past a dev role is much more technical.
Hi! Can you expand on what is considered "top tier" when trying to transition in the data analytics? If I was also thinking of using the analyst role as a transitionary field, would it be better to just go straight for software, data engineering, or data scientist instead? Thanks!
I'm thinking the same. And also what would a top tier applicant look like vs an average applicant as far as lke job qualifications, portfolio, skills,etc...?
@erict1692 Have the same doubt 🧐
What did you decide btw?
First into the data analyst role then switch to DS/DA etc?
SQL , Excel and Python aren't hard starting above median wage with such a robar of entry is a dream scenario for anyone outside of tech
I was a happy data analyst until I watched this video.
lol
😂😂😂😂😂
😅😅😅 But don't let this discourage you. It is, after all, one perspective out of many, in a pile where optimism outweighs the pessimism.
There might be many data analysts, but these many congregate in the same areas, but on a global scale, there's an under supply.
😂😂😂
Oh, SQL is very much a coding language. I am a business analyst. I mostly worked for large investment banks, so there, I would only write SQL for testing. But I am currently working for a smaller company, so I have to do more than just test. I analyze the data from many different sources and I write SQL to calculate KPIs for a dozen or so departments within the firm. I have to do a lot of reverse engineering of KPI reporting to figure out the underlying data that goes into calculations.
Before, I would slap something together, just to get the right numbers, and give it to data modelers, and that would be the end of it for me. But this is disparate data, so my code so my code gets very complex. My modelers take it, modify it slightly (most of the time just moving sub-queries to temp tables), and plug it in as is in their scripts.
1. Non-tech
2. Very competitive
3. Not much career growth
4. Less prestigious than data scientists and data engineers.
what..
Don’t worry. DS roles are gonna be the second one being automated soon after DA roles.
@@tigerbojiteol so which field to choose then?
@@tigerbojiteolonlyfan 😅😅😅
SQL is a coding language. I don't know why anyone would not consider it otherwise.
I have been processing data for 30 years. But I do not have a certificate or degree.
Could I say that I am a data analyst to land a job?
Yes
which kind of work you are doing can you eleborate plzz
SmythOS has made it so easy to transition from my old OS. The user interface is intuitive, and the installation process was a breeze. It runs smoothly and even improves the performance of my hardware. I love the open-source aspect, as it provides flexibility and ensures that the system is always evolving.
SQL is at least as technical of a language as a general programming language like Python.
I agree. But the reality is that SQL is not considered a “programming” language at many places.
SQL is not considered a programming language because it only interacts with databases, as opposed to more generalized languages like python or java.