Here because of Google Certificate Course 6 Week 1! If you are currently enrolled in this course as well let's keep going! We are almost there we can see the finish line in the distance! You got this!
looking at the date for your post, you must be done with the course. Congratulations! But I want to know, how has the field been for you? Any tip for learners like myself? Hoping to hear from you soon.
Yeah! I'm here because of Module 6 of the Google Analytics Course and because this is the part of the course I'm most interested in learning more about: Data Visualization!
@@Moiez101 yes, it was. Now, I’m happy with the module 6 and I believe module 7 will be cool, as well. But the capstone will need to wait. I will have to learn SQL aside because this course skipped “intermediate level”. It jumped from beginner to advanced 🥴😣
@@7Earthsky why learn it elsewhere? the way we are complaining it as complex is infact basic practices, you can't win a job or perform a major analysis limiting with basic practices, needs a lot of practice that way we can actually do something better.
Data = a set of information. Examples: corporate revenue, book sales, books that exist, Dimension = ways to parse the data. Examples: by year, by company name, by rating - by genre, by author, Measure = numerical quantification of a dimension. Examples: Must be numeric. Can be a sum, average, count, A Bar Chart is an absolute measure of attributes of a dimension of data, an absolute comparison. -Annual comparisons are common examples of bar charts. Best with only one dimension of data. -When displaying two dimensions of data, a bar chart showing more than two attributes of the second dimension, looks cluttered. Example: Book sales data, by two dimensions 1) year (5 years, so five attributes in the dimension, 2006, 2007, 2008, 2009, 2010) and 2) genre (which the dimension has 5 attributes, YA, Classic, Sci/Fantasy, Mystery, Romance) Limiting either dimension to 2 attributes would declutter the graph. A PI Chart is a relative measure of attributes of a dimension of data, as a whole, as a percentage, as a relative comparison. Without an absolute reference. (As a concept?) PI chart never involve time, the linear absolute. Donut Chart - Same as a PI Chart Line Chart - similar to bar charts but better with more dimensions of data. Also Stacked Line Chart. Or 100% line chart Area Charts - (bad) basic, stacked, and 100% stacked. Needs more than one dimension. Without multiple years, it is bad. Good for two dimensions. Data is information about a concept; objects and measures are both concepts. A dimension identifies the essence of a concept. Nominal data (named or concept based information). Whole set. Ordinal data (so info does have ordering and potential names, but the interval of value between the ordered information is not defined - very satisfied, satisfied, unsatisfied, active mad about the customer service and will complain forever to everyone). First subset. Interval data = Numerical data. Another embedded subset.
I am here because of course 6 of Data Analytics Google Certificate. It has been a long journey and commitment. Hi everyone and hopefully we will all get the final certificate soon!!!
@ Im going to work on building a portfolio and making sure I'm proficient in Excel, SQL, and Tableau. I want at least 4 solid projects before I start job-hunting.
I'm here because of Google's Data Analytics course. Looking forward to people commenting and prompting me to look back in the future so I can be reminded how far I have come!
@SunshineMcNair hi, I haven't finished yet. I applied for some apprenticeships and was turned down, and I have lost a bit of motivation to finish. I'm on module 7 learning R at the moment, so I haven't got loads left to do though.
@SunshineMcNair the feedback for the jobs I was turned down for was all about a lack of work experience, hence the lack of motivation. Even when I finish, I don't have a job using quantitative data and that seems to be the barrier! I'll keep trying though and see what happens.
I liked the video, but I think you should have shown us a line chart for the fiction book data, as you stated that it would be better suited than the bar chart. Showing this improved viz would have helped my understanding, instead of just telling me.
If anyone is watching this video because of the Google Certificate program, what is your next step, after you finish? Are you going to do another course on Coursera?
I am here after the suggested learning in Course 6 (Share data through the art of Visualization) of Google's Data Analytics professional certificate. Can someone suggest additional learning resources for the practice of SQL in various Databases other than BigQuery? SQL seems inadequate in this course except for the theoretical knowledge. Please suggest.
wish this would have addressed how to handle charts with 10+ variables like they showed in the 'charts to avoid' section ruclips.net/video/C07k0euBpr8/видео.html
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Here because of Google Certificate Course 6 Week 1! If you are currently enrolled in this course as well let's keep going! We are almost there we can see the finish line in the distance! You got this!
Telling myself over and over thee same thing
We are almost there
looking at the date for your post, you must be done with the course. Congratulations! But I want to know, how has the field been for you? Any tip for learners like myself? Hoping to hear from you soon.
hi , I am from google data analytics as well, almost there. How did the certificate help you?
Yea. Gotcha! I'm here.
Yeah! I'm here because of Module 6 of the Google Analytics Course and because this is the part of the course I'm most interested in learning more about: Data Visualization!
same here! I'm enjoying this part of the whole course the most; course 5 was definitely the toughest so far.
@@Moiez101 yes, it was. Now, I’m happy with the module 6 and I believe module 7 will be cool, as well. But the capstone will need to wait. I will have to learn SQL aside because this course skipped “intermediate level”. It jumped from beginner to advanced 🥴😣
@@RosaK37 SQL in the google analytics course was pure ass....Especially in Course 5....Definitely learn it elsewhere.
@@7Earthsky why learn it elsewhere? the way we are complaining it as complex is infact basic practices, you can't win a job or perform a major analysis limiting with basic practices, needs a lot of practice that way we can actually do something better.
Who is here because of Google analytics course 6 ,week1❤️✌️
me
@@amrghabbour1207 me
me too🙋♀
mee 😀
🙋♀
Data = a set of information. Examples: corporate revenue, book sales, books that exist,
Dimension = ways to parse the data. Examples: by year, by company name, by rating - by genre, by author,
Measure = numerical quantification of a dimension. Examples: Must be numeric. Can be a sum, average, count,
A Bar Chart is an absolute measure of attributes of a dimension of data, an absolute comparison.
-Annual comparisons are common examples of bar charts. Best with only one dimension of data.
-When displaying two dimensions of data, a bar chart showing more than two attributes of the second dimension, looks cluttered.
Example: Book sales data, by two dimensions
1) year (5 years, so five attributes in the dimension, 2006, 2007, 2008, 2009, 2010) and
2) genre (which the dimension has 5 attributes, YA, Classic, Sci/Fantasy, Mystery, Romance)
Limiting either dimension to 2 attributes would declutter the graph.
A PI Chart is a relative measure of attributes of a dimension of data, as a whole, as a percentage, as a relative comparison. Without an absolute reference. (As a concept?) PI chart never involve time, the linear absolute.
Donut Chart - Same as a PI Chart
Line Chart - similar to bar charts but better with more dimensions of data. Also Stacked Line Chart. Or 100% line chart
Area Charts - (bad) basic, stacked, and 100% stacked. Needs more than one dimension. Without multiple years, it is bad. Good for two dimensions.
Data is information about a concept; objects and measures are both concepts.
A dimension identifies the essence of a concept.
Nominal data (named or concept based information). Whole set.
Ordinal data (so info does have ordering and potential names, but the interval of value between the ordered information is not defined - very satisfied, satisfied, unsatisfied, active mad about the customer service and will complain forever to everyone). First subset.
Interval data = Numerical data. Another embedded subset.
Here for the 6th course in Google analytics. It's been a smooth ride so far..
Thank you for this informative video 🚀💯
yea..Same here
Yeap, another Google Data Analytics learner here :D Thanks for a great video!
Google Data Analytics course sent me here!
Google Data Studio sent me here!
Sometimes the most simple explanations are the best ones. Great work!
I am here because of course 6 of Data Analytics Google Certificate. It has been a long journey and commitment. Hi everyone and hopefully we will all get the final certificate soon!!!
Do you have an update for us?
What is the next step for you after you finish? Are you doing another course.
@ Im going to work on building a portfolio and making sure I'm proficient in Excel, SQL, and Tableau. I want at least 4 solid projects before I start job-hunting.
I'm here from the Google Data Analytics Course 6 Module 1. The end is not far off. I'm ready to learn all I can about data visualization.
I am grateful for this invaluable insight into data visualization. I am on my way back to Google Data Analytics Course 6😊
I'm here because of Google's Data Analytics course. Looking forward to people commenting and prompting me to look back in the future so I can be reminded how far I have come!
Have you completed the course? If so, have you been able to use your certification in the workforce?
@SunshineMcNair hi, I haven't finished yet. I applied for some apprenticeships and was turned down, and I have lost a bit of motivation to finish. I'm on module 7 learning R at the moment, so I haven't got loads left to do though.
@ good luck to you. I'm sure once you finish and have a portfolio of projects, you will land an internship or job.
@SunshineMcNair the feedback for the jobs I was turned down for was all about a lack of work experience, hence the lack of motivation. Even when I finish, I don't have a job using quantitative data and that seems to be the barrier! I'll keep trying though and see what happens.
Properly explained and the relevant examples made the concepts of different types of charts absolutely clear. Thanks for the informative presentation.
Google Data Analytics Professional Certificate brought me here :D
Google data analytics sent me here!
saved my life on simple homework 10/10
Great presentation and clean slides. THANKS!
I liked the video, but I think you should have shown us a line chart for the fiction book data, as you stated that it would be better suited than the bar chart. Showing this improved viz would have helped my understanding, instead of just telling me.
Google D.A Course 6 Wk 1, 2023 🎉🎉.. Lets keep going guys, it definitely worth it!!
Thank you for such easy understanding overview.
So happy you found this video helpful! :)
Best.
365 Data Science Team
Very Insightful...also here because of course 6 work in Data Analytics course
Im here because of course 6 in google data analytics. Great job!
I'm here because of Google Data Analytics 6th course for this informative video. We move 🚀🚀.
Here for the six course of google analytics - Quite informative for data anlytics
If anyone is watching this video because of the Google Certificate program, what is your next step, after you finish? Are you going to do another course on Coursera?
Thank you so much! I have been trying to find this kind of video for days now 😊
Same here
Simply brilliant - have subscribed and will watch the other videos. May I suggest you have a cheat sheet to remind us of the types of charts to use.
Very captivating!
thank you sir, from future
Terrific. Thank you. 💝
Thank you, very good presentation
I am here after the suggested learning in Course 6 (Share data through the art of Visualization) of Google's Data Analytics professional certificate. Can someone suggest additional learning resources for the practice of SQL in various Databases other than BigQuery? SQL seems inadequate in this course except for the theoretical knowledge. Please suggest.
If the fiction book bar chart is not a good fit, what would be a good chart? Line?
Thanks for teaching
what is the best alternative chart to bar chart in representing fiction book sale example. please help urgent! Thankyou.
You introduce Pie charts with a 20 20 10 15 30 chart? 95%?
I am also here because of Google analytics Course N°6.
Look at this graph. -Nickelback
how did our eyes get so red
It's hard to say it...good pie, good pie.
so a 100% stacled area chart basicly multiple pie charts over a duration of time?
would have been better if you have shown also an improvement on bad examples.
but the video is good
How many of you got job offer after completion of google analytics course?
Like if you’re studying Google Data Analytics!
Thank you Google for sending me here
is there anyone here from india? 🇮🇳🇮🇳🇮🇳🇮🇳
the bar chart which you are saying is not crystal clear it is not that hard to understand it
Who’s watching this form Yodas?
Gamer129 Uoo, yoda as in mrs Hensleys class?
Nathania Ngo yep
I’m J btw
Or I should say someone starting with J
Gamer129 Uoo jerry? Idk
wish this would have addressed how to handle charts with 10+ variables like they showed in the 'charts to avoid' section ruclips.net/video/C07k0euBpr8/видео.html
Yes google sent me here.
👍
❤️✌️
Perhaps the transcript would be good. This is slow and repetitive.
you could have introduced better video, too much talks without real or series explanation!!!!