Businesses today know that the answers to the most complex questions lie within their data. Can an insurance company identify fraudulent claims before they surface? Can a retailer identify a customer’s need for a loan in order to complete a purchase? Can an airline identify a customer that is about to shift loyalty? Can a broker move closer to predicting the movement of a certain script? Can a hospital predict a re-admission and prevent it? These are questions that would have foxed the most experienced, but they need not any more. Answers are in our hands, made possible by in-database analytics, a science that is being led by a new generation of ultra-sophisticated data appliances.
Data appliances are purpose built. They come loaded with hardware, software, analytical models and are designed to address exactly what you want your data to deliver. And they do everything several times faster than traditional methods, practically with zero latency. This, of course, brings into question the role of your traditional enterprise data warehouse (EDW) and its future - which, we can safely predict, is going to be over shadowed by data appliances.
Traditional EDWs are handicapped as far as today’s business needs are concerned. EDWs are slow and laborious, have security vulnerabilities, can prove to be expensive and are unable to scale and meet the growing diversity/ volumes of data. However, most of all traditional EDWs and analytical methods use data sampling, leading to less than optimal results. On the other hand, modern database appliances use complete data sets to arrive at near-perfect and dependable conclusions.
At the core of the efficiency of data appliances is their access to parallel processing power and a shared-nothing architecture. Data that took weeks to process can now be managed by these number crunching beasts in minutes. No business should even think about building new capabilities or taking decisions without the assistance of data appliances. They are the new pillars on which to build your digital world.