How to Analyze Data - A Step by Step Guide

[@drivetrainerYT]

Great video, wish clients possessed this understanding or at least eagerness to find out what is the use of collecting structured data and analysing it for business

[@absentdata]

Yes sometimes you have force clients to a part of the total process to get to the insights they are looking for.

[@ronenTheBarbarian]

Great Video! I think for a follow up video, it would be interesting to take this further and apply to diverse types of analysis used today in different areas. User analysis, product analysis, financial analysis (dealing with profit/revenue), marketing analysis (related to campaigns etc.), fraud analysis, stock market analysis, are all different 'worlds' I had to work in as a data analyst, with varying degrees of involvement, and being involved in different stages of the data analysis phase. Example for user analysis/behaviour: - User Behaviour with a website/product: Step 1 could be like "Why do 30% of our subscribers drop at the end of the year". The question can come from leadership, or it is something you will notice before anyone else and will have to tackle it. Step 2 could be "Success would be Subscriber who is retained after the end of year" Step 3: What trends should we measure for this? We should be looking at logins (active logins) of subscribers who drop, and subscribers who are retained. Or we can look at what premium features are being used by retained subscribers, and what is the engagement like for subscribers who drop? Do any of the dropped subscribers run into any technical issues? Do any of them contact customer support for any assistance with these features? Step 4: Events needs are login event, active flag or condition (customer signed in at least once in the past 30 days), what areas of the website/product they interacted with, so actual URLs or component names Step 5: The audience in this case product manager, senior leadership, etc. Just trying to think of how this amazing guide can be applied to real-world scenarios out in the field. I completely agree with you that one must sometimes force clients to be a part of this, but other times, we are "stuck" on our own to come up with baselines/hypothesis with no guidance or existing KPIs in place. I think analysts would benefit greatly if they knew about all the different areas they can work in, along with the data "dialect" in each area. Hope that made sense.

[@absentdata]

What a great comment. I loved how you added the structure of the data analysis framework to the various scenarios.

[@method341]

Great video. What app did you use to make your slides?

[@absentdata]

Thank you. Actually it was all done in PowerPoint

[@watcherme2]

nice video, can u recommend book or more details? thanks😊

[@absentdata]

Head First Data Analysis is a great book for the fundamental data analysis