Big data initially was characterized in terms of “the three V’s,” volume, velocity and variety. Nearly five years ago I wrote about the three V’s as a way to explain why new and different technologies were needed to deal with big data. Since then the industry has tackled many of the technical challenges associated with the three V’s. In 2017 I propose that we focus instead on a different letter, which includes these A’s: analytics, awareness, anticipation and action. I’ll explain why each is important at this stage of big data evolution.
The big data market continues to evolve, as I have written previously. Vendors are attempting to differentiate their offerings as they seek to encourage customers to pay for technology that they could potentially download for free.
IBM recently held its inaugural World of Watson event. Formerly known as IBM Insight, and prior to that IBM Information on Demand, the annual event, attended by 17,000 people this year, showcases IBM’s data and analytics and the broader IBM efforts in cognitive computing. The theme for the event, as you might guess, was the Watson family of cognitive computing products. I, for one, was glad to spend more time getting to know the Watson product line, and I’d like to share some of my observations from the event.
Topics: Big Data, data science, Machine Learning, cloud computing, cloud computing, Business inteligence, Data Governance, Data Integration, Internet of Things, Information Optimization, analytics, analytics, Machine Learning and Cognitive Computing
Ventana Research has newly published its Mobile Analytics and Business Intelligence 2016 Value Index. The Value Index provides a comprehensive evaluation of vendors and their product offerings across seven categories. In performing that analysis, I realized that this software category is at a crossroads. Once an optional capability often reserved for executives, mobile analytics is becoming a requirement of business users across organizations. The blurring of lines between work and personal lives has provoked a change from single device BI to BI on multiple devices including smartphones and tablets as well as laptops and desktops. From a platform standpoint, the adoption of HTML5 is contesting the prevalence of native mobile applications.
Data virtualization is not new, but it has changed over the years. The term describes a process of combining data on the fly from multiple sources rather than copying that data into a common repository such as a data warehouse or a data lake, which I have written about. There are many reasons for an organization concerned with managing its data to consider data virtualization, most stemming from the fact that the data does not have to be copied to a new location. It could, for instance, eliminate the cost of building and maintaining a copy of one of the organization’s big data sources. Recognizing these benefits, many database and data integration companies offer data virtualization products. Denodo, one of the few independent, best-of-breed vendors in this market today, brings these capabilities to big data sources and data lakes.