JUNE 2017CIOAPPLICATIONS.COM 19e're at an interesting moment of technological advancement today. It feels like there's barely time to digest the impact of new announcements before the next one has us scrambling to understand its impact on our business. And behind the most important innovations in the last several years--as well as the most innovative new companies--is data, the foundation for everything to do with business analytics.It's no wonder why analyst firm IDC states that by 2020 organizations that analyze all relevant data and deliver actionable information will achieve an extra $430 billion in productivity gains over their less analytically-oriented peers.This particular moment is shaped by the remarkable confluence of several factors happening simultaneously. Each one not only impacting the others, but also extending to far-reaching corners of the enterprise in ways we hadn't yet considered. These five factors are:· Rapid advancements in robotics and sensors, which are perhaps the most data gathering and data generating innovations we've experienced so far.· An over abundance of data, both within and especially outside the enterprise, which will continue to grow at exponential rates.· Impressive advances in computational capacity and cloud computing, which make it easier and more affordable for us to manage, visualize, share insights, and predict outcomes on all this data.· A fast-growing base of digitally-engaged customers, who expect more meaningful connections from our businesses in every interaction and transaction.· An increasingly connected workforce, with growing needs for immediate access and the power to be productive wherever they are, regardless of the type of device they use.As a result, data is now managed as an asset and analytics platforms are an even more strategic investment in all types of organizations. So it's only natural for us to ask what's next for business analytics.The answer is adaptive intelligence. Adaptive intelligence is an evolution of business analytics, and the two are complementary. Table 1 contrasts the focus (Pg 20).It's important to note that adaptive intelligence is the intersection of people judgment and machine automation. While machines can ingest more data in one second than what people can in ten years without forgetting it and without fatigue, and while automation greatly simplifies repetitive computational deductive or inductive processes, we cannot replace human reasoning. The ability to understand and adjust analytical models' inputs and training data, improve data imperfections, and apply ethics to our use and interpretation of data are a few examples of what machines can't completely replace.This relationship creates many new opportunities, such as being able to have a much improved real-time understanding of our business, greater ability to test ideas and hypotheses with unprecedented ease and speed, and much refined forecasting accuracy even as volatility and fast-changing conditions increase.Artificial Intelligence and machine learning solutions are based on algorithms that can learn from data without relying on rules-based programming. They can redefine how we interact with information and transform how we both work and live. For example, ADAPTIVE INTELLIGENCE: ANALYTICS' NEXT STEPcXoinsightsWRICH CLAYTON, VP, BA & BIG DATA, ORACLEJOSE VILLACIS, SENIOR GROUP MANAGER, CLOUD PRODUCT & BIG DATA, ORACLERich Clayton
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