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
Financial services organizations face considerable challenges today. From regulatory changes to globalization to shifting customer expectations, the urgent need to re-engineer outdated systems to better manage vast amount of data can apply additional pressure. Organizations must deal with the
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
Together, IBM and Cloudera offer a modern data platform with the governance and security to drive the future of AI and ML. Our solutions are optimized for the cloud, but we give our customers options to put their data where it works best for them.
Back when I was in school, one of the most difficult classes for my business degree was quantitative analysis. It wasn’t just hard, it was laborious to translate and solve business conditions and problems into algebraic equations by hand. In the beginning, it was merely optimizing output based on a
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”