Fast Data and the New Enterprise Data Architecture
Big data is indeed transforming the way enterprises interact with information, but that’s only half the story.
A structural shift in data management is underway. Unlike previous eras of technological change—mainframe to server, server to PC, PC to mobile and tablet—this shift is not driven solely by growth in processing power (the oft-cited Moore’s Law). Today, processing power is cheap at the endpoints. The combination of cheap, ubiquitous CPUs attached to fast mobile networks is creating a network effect of devices, distorting Moore’s Law with the force multiplier of near-global wireless network coverage. Thus, today’s shift is spurred not only by increases in processing power but also by the growth of data—of new data, which is doubling every two years—and by the rate of growth in the perceived value of data.
These macro computing trends are causing a swift adoption of new data management technologies. Open source software solutions and innovations such as in-memory databases are enabling organizations to reap the value of realtime interactions and observations. No longer is it necessary to wait for insight until the data has been analyzed deeply in a big data store. This is changing the way in which enterprises manage data, both data in motion—”fast data” streaming in from millions of endpoints—and data at rest, or “big data” stored in Hadoop and data warehouses.
Businesses in the vanguard of this change recognize that they operate in a “data economy.” These leaders make an important distinction between the two major ways in which they interact with data. This shift in thinking has led to the creation of a new enterprise data architecture. This book will discuss what the new enterprise data architecture looks like as well as the benefits it will deliver to organizations. It will also outline the major technology components necessary to build a unified enterprise data architecture, one in which both fast data and big data work together.