March 16, 2018 is the 25th anniversary of the Db2 relational database product on Linux UNIX and Windows. Over the past 25 years, this team has built the Db2 brand for the distributed product, complementing IBM’s Db2 mainframe offering and creating a market force.
Human beings tend to filter out events they deem unimportant. They can only process so much at any given time. Computer systems, however, must be able to handle a massive number of events in real time or near-real time to help support a wide range of applications.
Augmented reality (AR) and augmented intelligence systems such as Watson are breaking data outside the confines of a two-dimensional monitor and putting them into a three-dimensional visualization format. Big Data and Analytics Hub spoke with IBM AR designer Ben Resnick about what’s next for
For decades, a company’s database usually had a single job: operating as either an operational — also known as transactional — database or acting as a data warehouse. It was also typically deployed in a single location: on premises. Today, companies not only want more from their databases, but also
While the proliferation of data will be readily apparent, deciding what to do in response will be less straightforward. The majority of workloads currently sit in traditional, on-premises environments but we’ll see many of them move to private and public clouds over the next over the next five
With businesses requiring foresight into emerging technologies and relying on nimble responses, successful architects must know how to get the most of their data infrastructure and build for the future. That’s exactly why they need to set aside a few days in March to attend Think 2018 in Las Vegas.
Empowered and humbled: that’s the roller-coaster, sweet-and-sour ride I’m on when I attend Think. I’m empowered and emboldened to follow my dreams and push the boundaries of what’s possible. I’m humbled, realizing how far I have to go to push my own boundaries and myself.
Machine learning is being used at the heart of next- generation methods for self-driving cars, facial recognition, fraud detection and much more. At IBM, we’re applying machine learning methods to SQL processing so databases can literally learn from experience.
Your business and your data are both unique. For that reason, your enterprise architecture must also be tailored to fit the exact needs of your business. When data is involved, you want choices, not trade offs. And, more importantly, you want your solutions to build upon and complement one another.
When you wake up, the last thing you want to ask yourself is, “What did my data do last night?” CDOs who find themselves asking that question can put a stop to it on March 19. IBM is bringing experts and leaders across data governance and integration to the annual Think conference.