This week's guest is Jorge Castanon, a senior data scientist for Watson Studio at IBM. Host Al Martin and Jorge discuss some typical data problems currently plaguing the industry -- and how Watson Studio makes dealing with those problems that much easier. Get ready for an in-depth, technical
This week, host Al Martin welcomes Rakesh Ranjan, the director of emerging technologies at IBM Data and AI. He also works on next gen-solutions at IBM and is involved with academia and research. Join us for a look at what's next in data and AI.
According to a recent IDC report, 79 percent of enterprises are currently investing in a hybrid cloud environment or have planned to invest in towards one in the next twelve months. More businesses are looking to do this by adopting public cloud deployments for their data management needs.
It’s been one year since we launched IBM Cloud Pak for Data (previously IBM Cloud Private for Data), IBM's data and AI platform for today's modern enterprise. Since then, this platform has been embraced by hundreds of customers, and Forrester ranked it No. 1 in their “Enterprise Insights Platform”
Before making any major purchase decision, most of us read reviews to learn about the experiences of other users and get an understanding of a product from the perspective of the marketplace. This is especially important for when evaluating options for a major investment like planning software.
Intel's Melvin Greer, Senior Principal Engineer and Chief Data Scientist, Americas writes about the data strategy necessary to execute the promises of AI and touts their collaboration with IBM on Cloud Pak for Data. But before anyone can execute an AI strategy, they’ll need a data strategy.
IBM Cloud Pak for Data System is an integrated end-to-end platform that is cloud native by design, architected as microservices and containerized workloads. It offers instant pre-assembled provisioning and has capabilities to collect, organize and analyze data. It takes the IBM Cloud Pak for Data
There is no AI without data. That’s why we’ve put together a prescriptive set of five steps we call the ladder to AI to help our enterprise clients get their data ready. The journey of the AI ladder starts with collecting the data you need to build models, followed by organizing your data so you
A modern data architecture (MDA) must support the next generation cognitive enterprise which is characterized by the ability to fully exploit data using exponential technologies like pervasive artificial intelligence (AI), automation, Internet of Things (IoT) and blockchain. In addition, an MDA
Companies are entering “chapter two” of their digital transformation. The next chapter is all about moving from experimentation to true transformation. It’s about gaining speed and scale. We are helping businesses activate data as a strategic asset, with desire to maximize the impact of AI as core