Data analysis is abstract. It is not math (although math is involved) and it is not English or accounting. It requires a hands-on approach to truly understand the pitfalls good analysts will run into.

Yet, most students have not dealt with vague parameters and large data sets by the time they get their first job, which is a shame! Many students haven’t even heard of a data warehouse and this is where most of the data, which helps managers make critical decisions, resides.

In the modern business world, data analysis is not limited to data scientists. It is also key for analysts, system engineers, financial teams, PR, HR, marketing, and so on.


If you enjoyed this video, check out some of my other top videos.

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0:00 Intro
2:15 Set Up A Clear Data Analytics Process
4:56 Don't Bury The Lede
6:39 Data Analytics Peer Review
8:51 Triple Check Your Data
11:46 Know When To Stop Your Analysis
13:05 Recap

Tags: Data engineering projects, Data engineer project ideas, data project sources, data analytics project sources, data project portfolio

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About me:
I have spent my career focused on all forms of data. I have focused on developing algorithms to detect fraud, reduce patient readmission and redesign insurance provider policy to help reduce the overall cost of healthcare. I have also helped develop analytics for marketing and IT operations in order to optimize limited resources such as employees and budget. I privately consult on data science and engineering problems both solo as well as with a company called Acheron Analytics. I have experience both working hands-on with technical problems as well as helping leadership teams develop strategies to maximize their data.

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