The potential of big data is immense. Remove constraints on the size, type, source and complexity of useful data, and businesses can ask bolder questions. Technology limitations that once required sampling or relied on assumptions to simplify high-density data sets have fallen to the march of technology. Long processing times and dependencies on batch feeds are being replaced by on-demand results and near real-time visibility. Processing becomes focused on flows vs. stocks of data. External and unstructured data have moved from indecipherable black boxes to sources rich with insight. Web logs, social media streams, RFID and other sensor data, click-streams and a host of other sources can be used for practical business advantage. This transformation changes the questions that can be asked, but it also requires new tools and techniques to get to the answers.
|Technology’s aim: Better, longer life
The fountain of youth, it turns out, exists not in some distant, exotic land but right here in that vast repository of information known as big data.
|Two dogmas of big data: Understanding the power of analytics for predicting human behavior
The vogue for big data obscures the fact that the economic value of analytics projects often has as much to do with the psychology of de-biasing decisions and the sociology of corporate culture change as with the volumes and varieties of data involved.
Additive manufacturing paths to performance, innovation, and growth.
|Data: A growing problem
There’s no dispute, data volumes are growing exponentially. Huge amounts of data are generated every hour of every day, and this data comes from an ever-increasing variety of sources. It also captures growing volumes of increasingly complex data about customers, suppliers, and operations.
|The insight economy: Big data matters – except when it doesn’t
For a lot of executives, big data is the land of false promises and lost dreams – another overhyped trend in a long line of trends-that-weren’t. If you’re ready to skip past all the paradigm-shifting, game-changing clichés about big data and get to the stuff that matters - we’ve developed a guide to help get you started.