The best data catalogs can automate the process to collect, classify and profile data to ensure the highest standards of quality. Here are three popular use cases detailing why companies are moving towards IBM’s Watson Knowledge Catalog.
Artificial intelligence and machine learning (ML) have become very popular recently due to their ability to both optimize processes and provide the deep insights that push enterprises and industries forward. In fact, 68 percent of respondents in a recent 451 Research Report, Accelerating AI with
Machine learning (ML) is rapidly helping businesses derive better insight and optimize their day-to-day operations. Yet an ML model is only as good as the data used to train and continually improve it. With the majority of enterprise companies already using a hybrid cloud, accessing domain-specific
The fusing of analytics with leading technologies can unlock significant business value and bring new transformation opportunities for enterprise companies. In order to be successful, analytics-based initiatives such as AI and the Internet of Things (IoT) need massive amounts of big data—and also
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
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