Book recommendations

Here are some book recommendations in the field of data analysis, Business Intelligence (BI) and data visualisation. These are books that we have found useful, which we recommend to our students. If you are not in the UK, just click the thumbnail image and then change the location to your local Amazon site. (E.g. if you are in the US change Amazon.co.uk to Amazon.com.) Make sure to leave the rest of the URL unchanged.

The books are roughly in order of sophistication or experience, from books on Excel at the beginning, through Business Intelligence to general data visualisation.

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Excel 2019 Bible

Mostly data analysts seem to want training in Power BI nowadays. But, although it’s not as sexy, Excel is still the general purpose workhorse of the data analyst. Knowing Excel really well also helps the transition to Power BI because Power BI’s DAX language is based on Excel’s function language. So your bookshelf would be incomplete without an Excel manual that doubles as a heavy doorstop (1,120 pages).

John Walkenbach has made a career writing huge reference books on Excel for years, which have sold well because his writing is very well structured and extremely clear. His ‘Excel 2019 Bible’ with co-authors Michael Alexander and Richard Kusleika, is a recent version of the Excel overview. It includes formulas and functions, making charts, pivot tables and what-if analysis, working with Power Query and the data model and an introduction to VBA programming.

Don’t try to use it as a course. It’s a reference book.

There are also two other series of books by the same authors entitled Excel 20xx Formulas and Excel 20xx: Power Programming with VBA, which are also very good. The Formulas books have more details on difficult formulas including things like cube and array formulas.

Power Pivot and Power BI

‘Power Pivot and Power BI’ by Rob Collie and Avichal Singh is an excellent introduction to using the DAX language to make DAX formulas. It bridges the gap between the Power Pivot Excel add-in for managing the data model in Excel and its big sibling Power BI.

It is not very advanced in its treatment of DAX and doesn’t go into the time intelligence functions in much detail but it gives a great grounding on the concept of row and filter context and how the CALCULATE function works. So it is great if you are in your first year of learning Power BI. Clear and well written.

M is for (Data) Monkey

Users of Power BI also need a copy of this excellent book on Power Query, Microsoft’s ETL (Extract, Transform and Load) tool that is embedded in Power BI and Excel. ‘M Is for (Data) Monkey’ by Ken Puls and Miguel Escobar is a manual on how to use Power Query and not as much about the M language as one might expect from the title. It is also useful for users of Power Query who are not heavy programmers.

M is (how can I put it politely?) a challenging language and, if ever there was a language that needed a book written about it, M is it. For example it is case sensitive, so if you write ‘Null’ rather than ‘null’ you will get an error. This book should help to avoid loss of hair, damaged computer keyboards and even marital breakdown. Well worth the price.

Exam Ref PL-300 Power BI Data Analyst

Microsoft’s official book for preparing for the Power BI Data Analyst PL-300 exam.

It doesn’t come with practice papers, which seems a bit stingy. The one below is probably a better buy.

Microsoft Power BI Data Analyst Certification Guide

A more expensive preparation for the PL-300 exam but which contains two complete practice exam tests. Unless you are strapped for cash, I would go for this one as an exam prep book.

However, note that there are various free practice papers online. See the links under exams and certification.

The Definitive Guide to DAX: Business intelligence for Microsoft Power BI, SQL Server Analysis Services, and Excel

A much more thorough treatment of DAX than the ‘Power Pivot and Power BI’ book.

It is written by Marco Russo and Alberto Ferrari, two of the Power BI authorities who you can find on the SQLBI channel on YouTube talking about PBI itself and also explaining DAX Studio.

Authoritative and quite advanced.

Storytelling with Data: A Data Visualization Guide for Business Professionals

The author Cole Nussbaumer Knaflic is one of the current Data Visualisation experts. She developed her approach to data visualisation while working for Google and has a refreshingly radical attitude to it.

This is a fairly small book for once (267pp.) and puts data visualisation into a loose framework designed to focus on clearly communicating messages about the data. ‘Simple beats sexy’ she says. One of the few data-viz books I would recommend reading all the way through. Highly recommended.

The Visual Display of Quantitative Information

‘Power corrupts, PowerPoint corrupts absolutely,’ Edward Tufte.

This is the classic text to have on your coffee table if you are in data-viz and decide to invite your mates round for a Power BI party. (Sorry, ex-students for recycling this old joke so many times!)

The first edition was published before personal computers so it’s quite old now, but it is full of beautiful pictures and will get you thinking about principles of data-viz. It encourages you to tear up the rule book and start from scratch.

Tufte was the pioneer who coined the term ‘chart junk’. Also look up what he means by a ‘duck’.

FlowingData.com Data Visualization Set

Here is a pair of practical books on data-viz by Nathan Yau, who runs the amazing FlowingData website.

Visualize This, published first, contains many code snippets in R. If you are interested in making Power BI reports that use R scripts this gives you plenty of examples to learn from.

The second book Data Points looks at methodology and could, perhaps, have been given a more exciting name. Mustn’t grumble though, the content is good.

Key Performance Indicators (KPI): The 75 measures every manager needs to know

An early question for people working in Business Intelligence (BI) is: what are the metrics that we should be measuring? This book provides a handy reference list of 75 KPIs grouped into categories like finance, customers, marketing and sales, operations and supply chain, etc.

For each indicator the book explains why it is important, and how to set benchmarks. Even if you work in an area that needs slightly different KPIs, this list provides an excellent generic framework to start from.

Invaluable if you are working as a consultant in multiple markets.