5 books on data analytics you should read

To help you in your continuous professional development here are 5 books that might expand your knowledge on what data analytics can be.

5 readings on data analytics

Part of what constantly makes us better professionals —and sometimes, even better human beings— is our ability to learn. Sometimes learning comes through practice and workshops and “just doing it”, but sometimes it comes from a more theoretical standpoint. In short, sometimes it just comes from reading, and that is a habit we should cultivate (in case we are not doing it currently), and take care of (if you are already an avid reader).

This obviously applies to data and, in this case, data analytics, to be more specific. But to make the homework a bit easier, we’ve already helped with choosing some insightful readings that might expand your knowledge in this area.

Too Big to Ignore: The Business Case for Big Data, by Phil Simon

The award-winning author and technology expert Phil Simon tells us something all of us in this blog post are already aware of: Big Data is here to stay. It is, as the title says, impossible to ignore, and this book efficiently demonstrates without a lot of technicality —which is great for people curious about the subject but not necessarily already an expert about it— but plenty of use cases, quotes, and analysis why it is such a big deal.
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Data Analytics Made Accessible, by Dr. Anil Maheshwari

If you are looking for an academic experience, sort of a one semester course on data analytics and data science, this might be the book for you. Data Analytics Made Accessible actually keeps the promise of its title and teaches some basic concepts and skills so that everyone can then go on to more complex stuff with a very solid basis. This text is constantly being updated to keep up with times and the 2022 edition is already available.
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Storytelling with Data: A Data Visualization Guide for Business Professionals, by Cole Nussbaumer Knaflic

Okay, so you already know some of the ins and outs of data analytics, you can already explore it. Now what? Well, now you are going to have to know what to say with it. As the book description aptly puts it: “Don't simply show your data—tell a story with it!” Storytelling with Data: A Data Visualization Guide for Business Professionals teaches us how to develop a very niche but useful skill which is storytelling through data. You will start thinking more in depth about context, the right graphs for the right situation, how to make your audience gravitate towards what you believe to be the most important piece of data, and more.
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The Model Thinker: What You Need to Know to Make Data Work for You, by Scott E. Page

This one agrees with our last entry on one thing: having the data, the numbers, just isn’t enough. But while Nussbaumer takes somewhat of a more “narrative” approach —for lack of a better word—, Page’s The Model Thinker takes a deep dive into the mathematical and computational aspects of how to make data talk to you. If you are already familiar with data as a whole and want to explore more technical possibilities to get better results —be it better decision-making, designs or predictions—, this might be the text that you are looking for.
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Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking, by Foster Provost and Tom Fawcett

Perhaps the most well known book in this list, Data Science for Business is a must for everyone interested in the world of data. It is written by two world renown experts on the field and it is based on the MBA course Foster Provost taught for over ten years at New York University. A quick search through Amazon and Goodreads reviews will provide you with enough evidence on why this has been such an important text in the industry and why it will probably continue to be on reading guides like this one for years to come.
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