The best business intelligence books

Many authors have picked their favorite books about business intelligence and why they recommend each book.

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Cleaning Excel Data With Power Query Straight to the Point

By Oz du Soleil,

Book cover of Cleaning Excel Data With Power Query Straight to the Point

If you just want to find out if Power Query is for you, this short book, written by the entertaining host of the Excel On Fire YouTube channel will show you what is possible using Power Query. Oz will show you the types of everyday problems that can be solved using the Get & Transform section of the Data tab in Excel. Once you get a taste of what is possible, you will be ready to dive in with Ken Puls’ book.


Who am I?

I’ve been running the MrExcel website since 1998 and have written 66 books about Excel. I am an Excel generalist – I know a fair amount about almost every aspect of Excel. But I respect the specialists who become experts on one part of Excel and offer deep knowledge dives into those portions of Excel. Cleaning data with Power Query, calculating “impossible” calculations with DAX, and then presenting them on interactive dashboards are some of the deep dives that you will learn on this list.


I wrote...

Power Excel 2019 with MrExcel: Master Pivot Tables, Subtotals, VLOOKUP, Power Query, Dynamic Arrays & Data Analysis

By Bill Jelen,

Book cover of Power Excel 2019 with MrExcel: Master Pivot Tables, Subtotals, VLOOKUP, Power Query, Dynamic Arrays & Data Analysis

What is my book about?

657 Excel mysteries solved. Direct from MrExcel himself, Bill Jelen. If you use Excel 10, 20, 40 hours per week, you will save 50 hours per year with the tricks in this book.

Jumpstart Snowflake

By Dmitry Anoshin, Dmitry Shirokov, Donna Strok

Book cover of Jumpstart Snowflake: A Step-by-Step Guide to Modern Cloud Analytics

In industry, your data is very likely to live within a data warehouse such as BigQuery, Redshift, or Snowflake. Therefore, to be an effective data scientist in the industry, you should learn how to use data warehouses effectively. 

Once you learn data warehousing and SQL with any one of these products, it is quite easy to pick up another. So which one do you start with?

You can use Snowflake on all three of the major public clouds. Because it’s a standalone product, it is the most similar to a “traditional” data warehouse and can be picked up easily even if you are not familiar with cloud computing. That makes it a good data warehouse to start with, and is the reason my second book pick is this book on Snowflake.

BigQuery is also available on all three major public clouds, but it works best (and is used most commonly)…


Who am I?

I started my career as a research scientist building machine learning algorithms for weather forecasting. Twenty years later, I found myself at a precision agriculture startup creating models that provided guidance to farmers on when to plant, what to plant, etc. So, I am part of the movement from academia to industry. Now, at Google Cloud, my team builds cross-industry solutions and I see firsthand what our customers need in their data science teams. This set of books is what I suggest when a CTO asks how to upskill their workforce, or when a graduate student asks me how to break into the industry.


I wrote...

Data Science on the Google Cloud Platform: Implementing End-To-End Real-Time Data Pipelines: From Ingest to Machine Learning

By Valliappa Lakshmanan,

Book cover of Data Science on the Google Cloud Platform: Implementing End-To-End Real-Time Data Pipelines: From Ingest to Machine Learning

What is my book about?

This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on Google Cloud Platform (GCP).

Through the course of this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science.