Big data and analytics promise to change virtually every industry andbusiness function over the next decade. Any organization that gets started early with big data can gain a significant competitive edge. Just as early analytical competitors in the “small data” era (including Capital One bank, Progressive Insurance, and Marriott hotels) moved out ahead of their competitors and built a sizable competitive edge, the time is now for firms to seize the big data opportunity.
As this book describes, the potential of big data is enabled by ubiquitous computing and data gathering devices; sensors and microprocessors will soon be everywhere. Virtually every mechanical or electronic device can leave a trail that describes its performance, location, or state. These devices, and the people who use them, communicate through the Internet—which leads to another vast data source. When all these bits are combined with those from other media—wireless and wired telephony, cable, satellite, and so forth—the future of data appears even bigger. The availability of all this data means that virtually every business or organizational activity can be viewed as a big data problem or initiative.
Manufacturing, in which most machines already have one or more microprocessors, is increasingly becoming a big data environment. Consumer marketing, with myriad customer touchpoints and clickstreams, is already a big data problem. Google has even described its self-driving car as a big data project. Big data is undeniably a big deal, but it needs to be put in context.
Although it may seem that the big data topic sprang full blown from the heads of IT and management gurus a couple of years ago, the concept actually has a long history. As Stephan Kudyba explains clearly in this book, it is the result of multiple efforts throughout several decades to make sense of data, be it big or small, structured or unstructured, fast moving or quite still. Kudyba and his collaborators in this volume have the knowledge and experience to put big data in the broader context of business and organizational intelligence.
If you are thinking, “I only want the new stuff on big data,” that would be a mistake. My own research suggests that within both large non-online businesses (including GE, UPS, Wells Fargo Bank, and many other leading firms) and online firms such as Google, LinkedIn, and Amazon, big data is not being treated separately from the more traditional forms of analytics. Instead, it is being combined with traditional approaches into a hybrid capability within organizations.
There is, of course, considerable information in the book about big data alone. Kudyba and his fellow experts have included content here about the most exciting and current technologies for big data—and Hadoop is only the beginning of them. If it’s your goal to learn about all the technologies you will need to establish a platform for processing big data in your organization, you’ve come to the right place.