Choosing the right data management solutions as the foundation for AI is crucial. Enabling AI optimization and usability is paramount, as is easy scalability to accommodate the increasing amount of data used by AI applications. This is true no matter where you store your data: on-premises, in the
Nearly every business is under competitive, disruptive, and regulatory pressures. As companies face digital transformation and modernization to meet their customers’ expectations, leveraging data and AI at the speed of business can be the biggest differentiator.
However, according to MIT Sloan, 81
In my last blog post, I covered how you can deliver an AI pilot in just eight weeks and at the same time design your program in a way to scale the AI across your enterprise. Culture, architecture and technology is fundamental to move from AI pilot to AI @ Scale. I also discussed how IBM is helping
The best decisions are made by extracting value from all the disparate data across your business. Yet aggregating data across external sources, regional silos and various forms of storage is not an easy challenge to solve.
Data-powered businesses need always-on access to data to keep operations
For the past nine years, Stack Overflow, a question-and-answer website for programmers, has polled developers to understand what technologies they are using and to find out what technologies they want to work with next. This year, the nearly 90,000 survey participants revealed that, once again,
IBM continues to increase support for open source technologies. Today, we are pleased to announce that Cloud Pak for Data System now features a new capability for Postgres workloads—the IBM Performance Server for PostgreSQL.
In a previous blog, I explained how data science capabilities, massive parallel processing (MPP)
and usability improvements in data warehouse appliances can help the bottom line—and why old-fashioned architectures might not cut it. But what does that look like in practice?
Research firm Quark +
IBM’s integrated platform for Data & AI, which is 100% complimentary to Red Hat offerings. It runs on OpenShift today and has a hardware version called Cloud Pak for Data System. The beauty of Cloud Pak for Data is that it includes all of IBM’s strategic Data and AI services – including Watson
Today, IBM announced bold new moves that transform our software portfolio to be cloud-native and delivered as pre-integrated solutions called IBM Cloud Paks.
A key part of this effort is Cloud Pak for Data, a cloud-native, container-based data platform that enables IBM Watson to run Anywhere,
“In 2021, AI augmentation will generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity,” according to Gartner. It will do so largely by learning how to make better predictions over time and supplementing people’s ability to complete tasks in more natural ways
It’s no surprise: most companies working with stream data today say they are planning to make changes to drive greater value. Advancements in machine learning (ML) and very-high-speed data persistence for real-time analytics are reshaping strategies and architectures. In addition, 88 percent of