Roles in Data Science Teams
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- Опубликовано: 28 июн 2024
- Data-driven organization. You’ve likely heard this buzz phrase hundreds of times. But what does it really mean? And who are people who make data useful?
In our new video we’ll have a look at the real data infrastructure technology and teams that make it work.
00:00 Rating system change at Netflix
01:33 Data-driven organization
02:33 Data infrastructure and data engineering
05:52 Machine learning and data science
Sources:
[1] www.forbes.com/sites/insertco...
[2] / customer-obsession
[3] • Binging on Data: Enabl...
[4] newvantage.com/wp-content/uplo...
[5] hbr.org/2012/10/data-scientis...
[6] pdfs.semanticscholar.org/1eb1...
[7] towardsdatascience.com/data-s...
To learn more check our articles:
1) Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role www.altexsoft.com/blog/datasc...
2) What is ETL Developer www.altexsoft.com/blog/datasc...
3) How to Structure a Data Science Team www.altexsoft.com/blog/datasc...
4) How to Choose a Data Science and AI Consulting Company www.altexsoft.com/blog/busine...
Learn more about AltexSoft: www.altexsoft.com
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This video contains the frames from movies:
Pulp Fiction, 1994
Avatar, 2009
Friends, 1994 - 2004
The lion king, 1994
Interstellar, 2014
Click, 2006
Schindler's list, 1993
Blade Runner, 1982
Uncut Gems, 20190
Music in video:
• Ghost Dance by Kevin MacLeod is licensed under a Creative Commons Attribution license (creativecommons.org/licenses/...)
Source: incompetech.com/music/royalty-...
Artist: incompetech.com/
• Cherry Blossom - Wonders by Kevin MacLeod is licensed under a Creative Commons Attribution license (creativecommons.org/licenses/...)
Source: incompetech.com/music/royalty-...
Artist: incompetech.com/
• Evening Fall Harp by Kevin MacLeod is licensed under a Creative Commons Attribution license (creativecommons.org/licenses/...)
Source: incompetech.com/music/royalty-...
Artist: incompetech.com/
• Harlequin by Kevin MacLeod is licensed under a Creative Commons Attribution license (creativecommons.org/licenses/...)
Source: incompetech.com/music/royalty-...
Artist: incompetech.com/
• Prelude No. 16 by Chris Zabriskie is licensed under a Creative Commons Attribution license (creativecommons.org/licenses/...)
Source: chriszabriskie.com/preludes/
Artist: chriszabriskie.com/
• Constance - The Descent by Kevin MacLeod is licensed under a Creative Commons Attribution license (creativecommons.org/licenses/...)
Source: incompetech.com/music/royalty-...
Artist: incompetech.com/
• Accralate - The Dark Contenent by Kevin MacLeod is licensed under a Creative Commons Attribution license (creativecommons.org/licenses/...)
Source: incompetech.com/music/royalty-...
Artist: incompetech.com/ 
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This is superb and we sure need more of your content! Really, really good job - Kudos!
Very well explained in a simple and visual way. Thanks!
A very easy understanding visualization that helps any layman like me to understand the complex concept of data science and machine learning.
Your videos are amazing, I've been looking for a channel like this
Thank you so much. That was so helpful. I started creating a data science team in my job.
Very insightful
Great video. You broke it down very well. Thank you
Love all your videos related to data. Got a little worried when the last part mentioned that Data Scientist/BI work will be taken for granted and that it will become common to functionality in any given software. Does that mean that this role has limitations expanding to the future? Once all the models are trained and automated to be consumed , what next?
I think they mean that it will stop becoming exciting and futuristic, and more something part of normality - don't worry too much :)
Overtime Career Pathways or the Career itself will soon become overrated, that was what the narrator means by the last part.
We have started seeing few examples in Data Workspace, Visual Recommendations (based on the labelled dataset) ....... which greatly reduces analyst interference to analyse and communicate data by visualization.
Going Forward, it's best to start incorporating Data Automations, Advance Data Engineering or Pipelining and APIs to ........ design workable system without Humans interference
@@AShina-zn7nx Thanks for the reply.
Great video - I've done most of those jobs over the last 10 years. But you missed out Data Artist! Analysts are fantastic with numbers but often lack the User Experience skills that are supplied by a Data Artist.
I want to get into this field but that last line of this video bothers me. Will we really become redundant?
Powerfully captured 👍
Greate video! Thanks :)
juste perfect
Thanks for the video.
im studying machine learning and data science since pandemic begin.. and start to build my own system to seek opportunity in business, jobs etc. do you think i can make it own my own and got only associate degree in computer science. but i love what im doing and im excited to have the result of my work even it takes years.
Great video!
I am Azure Solution Architect, now I am interested to become a Data Architect 😊
Wish you luck, if you'll really ever try it)
i love this video
good video
IMO, Netflix's explanation is BS. In reality, removing the percentage rating is to provide the users less information about the content. This in turn pushes the customer to actually try that movie/show to see if they like it. On the other hand, with percentage rating, the customer will naturally avoid what they consider low rating, just like shopping on Amazon -- so in the whole, less viewing by the user.
0:26 Netflix removed ratings because a left leaning comedian, Amy Schumer, was getting downvoted to hell and created cracks on which opponents of wokness could climb the wall to freedom. The old rating made the difference between awesome movies people would actually paid for and sub-standard movies people watched "for free", due to the subscription system.
The video said Data science will die down because of automation. For quite some time now I have been saying I do not want to apply for a position as a data scientist. I want to apply as something else and use my data science skill. Why? Because of the same automation reason. You have to think ahead of all industries. Also, I do think the world will be in trouble if the governments allow companies to automate everything and a lot of thing. Jobs will be taken away and this can obviously cause economical and social issues. I think every business owner big or small should learn circulatory economic and how there actions affect municipalities, towns, cities, states, and the country.
We didn’t say that data science will die per se. It’s likely that DS will become one of the branches of software engineering.
As for automation, it’s completely normal and has always been around. And it’s not likely that automation will cause unemployment in the future. Automation normally doesn’t take over entire jobs. Instead, it takes over specific parts of a job structure, kind of like a calculator makes an abacus obsolete but doesn’t force an accountant to the street. Well, unless your job structure consists of a couple of simple operations.
Once some part of the job structure becomes automated, people can focus on the rest of their responsibilities and learn new skills. We have an old article breaking down this matter. Give it a look if you’re worried. www.altexsoft.com/blog/business/reality-check-robots-are-here-to-automate-your-job-or-not/
jobs are not taken by automation, they are only replaced by other kind of jobs, usually more specialized (meaning, better paid). Automation improves efficiency, and that results in greater profits for the companies. This allows better economical and social conditions, and higher average living standars.
Statistics is definitely easier to learn than the unending load of programming to learn.. Data scientists are basically leaching off of other experts with hard skills.