Addressing Business Challenges with Enterprise Analytics

Neural networks were originally conceived in 1943 but were largely put aside until the advent of sufficiently capable computing power to run these networks in the 1970's - we face the same challenge today but with data. Many organizations lack the capabilities to handle and combine the data they have in-house already to drive real business changing decisions, so how can they hope to be prepared for the future deluge of data that the growing connected world is bringing? Increasing automation of decision making (via event driven processing) and fierce competition within most industries is driving us all to make more decisions faster, if not instantaneously - a mirroring of the phenomenon that occurred within Wall Street with the advent of High Frequency Trading 25 years ago. Today, that same millisecond half-life value of data is prevalent across industries and much disruption can be oversimplified to increasing timeliness of insights from data. While in the past on Wall Street, this could be solved by paying to have a server located physically closer to data feed, the future of many industries brings the promise of a new problem where the required data is distributed. In this brave new world the timeliness of your entire data pipeline will ultimately determine the level of intelligent decision making you can apply. Attend the talk to see why as with the past, present and future - "it's about time". .