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
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
Is your business ready to harness the power of AI to unlock value from all your data? Are you just getting started on your company’s path to AI – or are you working to scale AI to more areas of your enterprise business?
Regardless of where you are on your journey to AI – you should consider
The event formerly known as IBM Analytics University is happening again this fall. Join us at the Data and AI Forum on October 21–24 in Miami, Florida. Here’s a preview of what you can get out of this exciting event.
For 2019, we’ve expanded the curriculum to include the entire IBM Data and AI
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
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,
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 +
“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
Capitalogix is a hedge fund, but it’s really a data science firm in disguise. They work to understand and exploit capital markets by building custom data science models that can analyze massive amounts of data from as many sources as possible. Capitalogix’s need for high-performance analytics and
Last year, more than 100,000 developers from 156 nations built 2,500+ applications in Call for Code 2018, an IBM initiative to create meaningful change through technology. This year, it's your turn. Join Call for Code 2019 and you’ll have the opportunity to create sustainable software solutions