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
From machine learning to blockchain to artificial intelligence, data is dominating the conversation in the tech industry. In the first episode of Data Decoded, William McKnight, CEO of McKnight Consulting, and Yves Mulkers, founder of 7wData and a data/business intelligence architect, discuss the
In this week's episode of Making Data Simple, Al Martin and Adam Storm, IBM senior technical staff member and master inventor, next-generation HTAP architect, sit down to talk about fast data. Adam also covers the pros and cons of different information architectures and the software you can use to
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.
How does artificial intelligence (AI) come into play on a day-to-day basis? In this episode of Making Data Simple, Jean-François Puget, distinguished engineer, machine learning and optimization, and Steve Moore, senior story strategist for Inside Machine Learning on Medium, join host Al Martin to
Data management is a discipline that's remained relatively unchanged and, to put it bluntly, somewhat stagnant over the past 10 or 20 years. Since the dawn of the Internet of Things (IoT), these trends have already reversed.
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 has joined artificial intelligence (AI) as the hottest technology topics of 2018. We asked our expert influencers to share their thoughts on the state of the industry: where it's going, and how and why companies should be adopting machine learning and AI.
Getting the most from a data science agenda requires more than data scientists. At Think, you’ll learn to view data science as a team sport, involving multiple roles and appropriate tools that help organizations tap into the benefits data science can bring wherever the business opportunity is.
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.
Technology trends and growth areas can vary in different parts of the world. In this week's podcast, Keichii Okada, vice president of IBM Tokyo Software & Systems Development Lab, discusses how natural language technology is helping to advance business strategy and healthcare in Japan. He also