The All England Lawn Tennis Club (AELTC) loves their data. During The Championships, Wimbledon, last year alone, IBM collected 4.5 million tennis data points covering every point in every match. In fact, the All England Club has data going all the way back to when The Championships started in 1877
In this week's episode of Making Data Simple, we are joined by guest John DeNero, who is a professor at UC Berkeley. John specializes in teaching artificial intelligence, and he won a distinguished teaching award in 2018. Host Al Martin and John discuss methods of teaching AI, the state of the
On June 12th, IBM debuted AutoAI, a new set of capabilities for Watson Studio designed to automate critical yet time-consuming tasks associated with designing, optimizing and governing AI in the enterprise. As a result, data scientists can be liberated to commit more time to designing, testing and
When businesses evaluate cloud infrastructure, databases or other core business systems, they nearly always consider scale as a decision factor. But scalability – the ability to grow as planning and business grows – is often overlooked for enterprise performance management.
So what do companies
While data is an enterprise’s most valuable resource when it comes to gaining competitive advantage and improving business performance, time is a critical component. Businesses run 24x7, tasking our data citizens to maximize actionable insights that will drive the actions of tomorrow.
In the latest episode of :"Stories from the Field," Host Wennie Allen, IBM Data and AI, sits down with Elenita Elinon, leader of the Quantitative Research Analytics at JP Morgan Chase, recognized and awarded as one of the top 40 Women Leaders in Data and AI for her work with risk and fraud. Elenita
In part one of the Capitalogix data science story, I focused on their strategic need for a data platform that supports speed, data variety and custom-built algorithms to find advantages for their business. A key success driver: they worked to make life better for the people on the front lines of
In my last blog, I stressed the need for a modern data architecture (MDA) to underpin the next generation of the cognitive enterprise, fully harness data using the latest technologies, and sustain a platform-centric business model that supports people, process and technology optimized around