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Algorithms to Live By is the equivalent of a breezy summer read, a guilty pleasure that anyone in the analytics field can gobble up and consume with great delight. The book’s subtitle, “The Computer Science of Human Decisions,” sounds dry but the book is anything but. By delving into detailed descriptions of the common human dilemmas we all face, the authors provide buckets of fascinating insight into how computers can help us deal with our daily preoccupations in a productive manner.
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Star Schema by Christopher Adamson is a clearly written and comprehensive book about the all important topic of dimensional design. The ability to create a database with a dimensional design is essential to all business intelligence endeavors, and permeates many analytical processes.
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New York Times reporter Steve Lohr borrowed the term “Data-ism” from fellow columnist David Brooks to express the increasingly important realization that the capabilities of big data have had a huge impact on both the practice of business and our daily lives. In this book, Mr. Lohr explores the fascinating human interest stories that lie behind this extraordinary wave of societal change.
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Thomas Davenport, author of the best-selling Competing on Analytics, has penned a follow-up book titled Keeping Up with the Quants. Written with co-author Jinho Kim, this new title focuses on the process of analytics, and on the realities of communicating with analysts who may have more quantitative skills than yourself.
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The focus of Now You See It lies at the intersection of data analysis and visualization. As described by its subtitle, “Simple Visualization Techniques for Quantitative Analysis,” the author’s purpose is to explain how visual charts and graphs can complement the process of data analysis by allowing the analyst to perceive patterns in data. Filled with many illuminating graphics, this book is well-researched, persuasive and just plain fun to read.
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It must be said that the current enthusiasm that surrounds “big data” is not all hype. The concept is based on reality, and this book explains why that is so. The authors note that between 2000 and 2007, the total amount of data stored digitally increased from 25% to over 90%. With this massive deluge of data, there has been a resulting paradigm shift in how one thinks about data. In fact, the authors coin the term “datafication” to describe recent attempts to utilize data in new and creative ways.
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Like a well-written play, Competing on Analytics grabs the reader’s attention and establishes the basic premise early in the first scene. In its first few pages, the authors relate the compelling story of how Netflix beat the odds and triumphed over the then dominant Blockbuster to capture the loyalty of those who rent movies.
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An ugly reality of Business Intelligence development is the immense effort that is required to build and maintain the data warehouses that lie behind such an endeavor, particularly when data is coming in from multiple sources. In a typical situation, this task requires the use of ETL software to load data into the data warehouse, while transforming it to the desired structure. There is an inherent inflexibility in the procedure, since any change in design requires altering the ETL and reloading data.
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