Book review: BIG DATA IN PRACTICE
How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results
Genres:
- Information management
- Data Science
- Data Analytics
Review posted on:
14.11.2021
The number of pages:
320 pages
Book rating:
2/5
Year the book was published:
First edition published 2016
Who should read this book:
- People who are interested in who and where is collecting data about their customers/users and what potential does that hold for the companies collecting this data.
Why did I pick up this book and what did I expect to get out of it:
I found this book at the library and I have to admit that the title was “eye-catching” from the start. If you are interested in Big Data or data in general wouldn’t you just love to pick up a book that will tell you how 45 successful companies use big data in practice? And on top of that, you will get to learn about the data analytics strategies that deliver extraordinary results. Now come on how can’t you pick up a book like that, right? So I borrowed the book, looked up some reviews, and information about the author, and even though the book had some bad reviews I decided to give it a go.
What I was hoping to get out of this book was insights on how and which data companies are collecting and what they are doing with that data to deliver those on the cover of the book mentioned extraordinary results. Not that I would be able to do the same, but at least to “look inside” the minds of people who are creating our everyday experiences based on data of which most people can’t make any sense. I wasn’t expecting step-by-step instructions but I was expecting mostly insightful case studies where maybe the author would share what worked and what didn’t, what were the “aha” moments, what was the thinking process behind the decisions about the data strategies, and so on…
My thoughts about the book:
Big Data in Practice by Bernard Marr at first glance looked very interesting, not just because of the title but also because of how the author structured the book. Each case study is its own chapter, and is “broken down” into the following sub-chapters:
- “Background”,
- “What problem is Big Data helping to solve?”,
- “How is Big Data used in practice”,
- “What were the results?”,
- “What data was used?”,
- “What are the technical details?”,
- “Any challenges that had to be overcome?”,
- “What are the key learning points and takeaways?”.
But after just a couple of chapters in I saw that even though the “design” of the book was what I was searching for the actual content was extremely poor. First of all the 45 chapters are like you would copy-paste 45 online quickly and poorly written articles into a book just to publish it. I see almost no value as the author just scratches the surface of each “case study”. There were a couple of chapters where the author actually wrote a little bit more about how and why the companies collected data but not much effort was given into explaining how data was used to make reports or any kind of predictions. I expected more information about the “in practice” part the author promised, but I ended up very disappointed, and even though there are many praises about his other books and work I am hesitant to ever pick up any of it.
The only reason that I didn’t rate this with one star is because of 3 “case studies” that actually offered some insights on why and how to collect data, what to do with it, and how the whole situation could evolve.
If you have read the book please let me know what you think about it in the comment section.
A short summary of the book:
What I liked about Big Data in Practice was that Bernard Marr thought through the structure of the chapters. Each chapter is its own “case study” of a certain company from its specific field. At first, you read the “background” of the “case study” so you have a “birds-eye view” of the situation. Sometimes this is written well, sometimes not. Then the author tries to explain what problem is Big Data trying to solve. Next is the question of how Big Data is used in practice in this case. And this is where the author has the chance to deliver so much value but in most cases, this is just a simple overview and a great disappointment for the reader in my opinion. To be honest, there are a couple of chapters that cover this question well but this is only in a couple of chapters that are very well known in the “analytics world”, for example, the “Netflix hackathon”, the Walt Disney “Magic Bands” and some more.
In “What were the results” and “What data was used” we again get just some short answers in a couple of lines which offer little or no insights into the subject at hand. When the author talks about the technical details and about the challenges that had to be overcome you again get maybe half a page to one page of content per chapter and with that as much (little) value. And now we come to the last question of each chapter, “What are the key learning points and takeaways?” Well, again the author offers little or no value by sharing some generalized thoughts about the subject of the chapter. In the 45 chapters that are in the book, you can read about companies from different industries (IT, cars, financial, sport, fashion, transport, social, gaming, and more…).
My notes from the book:
- Human interaction with data is just as valuable as the data itself. There is a danger that we place too much blind faith in data itself, when in fact, how we work with that data and make decisions based on it is the key.
- Working with just one dataset can provide a very one-sided view. Often it’s the correlations and interactions between different types of data that provide the real insight gems.
