I recently attended SAS Institute’s analyst relations conference. There the company provided updates on its financial performance and its Viya platform and a glimpse into some of its future plans.
Topics: Big Data, data science, Mobile Technology, cloud computing, business intelligence, Data Governance, Data Integration, Data Preparation, Internet of Things, Information Optimization, analytics, Machine Learning and Cognitive Computing, Mobile Big Data, Machine Learning Digital Technology, Collaboration for Business
Cloudera provides database and enabling technology for the big data market and overall for data and information management. As my colleague David Menninger has written, the big data and information management technology markets are changing rapidly and require vendors to adapt to them. Cloudera has grown significantly over the last decade and now has approximately 1,000 customers and provides support and services in countries around the world. Its product and technology strategy is to provide a unified data management platform, Cloudera Enterprise, that can meet the data engineering and science needs for a range of analytic and operational database applications. Its primary focus is its Enterprise Data Hub, which as a data lake can handle organizations’ big data and analytical needs. As David Menninger asserts, the data lake is a safe way to invest in big data. It also helps shift the focus away from the V’s (volume, velocity and variety) of big data to the A’s, which are analytics, awareness, anticipation and action.
Topics: Big Data, data science, Machine Learning, cloud computing, business intelligence, Data Governance, Data Integration, Data Preparation, Internet of Things, Cognitive Computing, Information Optimization, analytics, digital technology
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