Avoiding Data Pitfalls: How to Steer Clear of Common Blunders When Working with Data and Presenting Analysis and Visualizations

There are a lot of good books Power BI developer can read. It’s hard to select only 5 of them. But I decided that I’ll select 5 and create a new post “5 most useful books for Power BI developer”. They won’t be ranked from #1 to #5, they are about different topics, each of them is important and you have to read all of them. This book is not about ETL, data modeling, DAX or data visualization. But it’s very important book for every Power BI developer.

This book is very important for anyone who works with data analytics and visualization. You can install Power BI (any or other BI tool), you can become good in ETL, you can become good in data modeling, you can become good in DAX, R or other language. You can become good in visual representation of your data. But you can miss one of the pitfalls described in this book and you’ll fail. Your data visualization will be useless (not the worst case) or misleading. This will lead to wrong decisions, sometimes to very expensive wrong decisions. A data pitfall can ruin your project, damage your business, crash a spaceship.

I highly recommend this book to anyone who works with data. From a student to an expert. Ben Jones created a comprehensive list of data pitfalls (it will be a data pitfall to assume this is a complete list). Be aware of all the pitfalls listed in the book every time when you’re starting a new data project. Use the book as a checklist to make sure you’re no trapped in the pitfall. Avoid mistakes on the early stage, don’t expect you’ll successfully debug your report after completion. Keep this books on your table as a reference.

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