On this week's episode of Making Data Simple, we talk about the future of AI, machine learning, and Watson with Steven Astorino, VP of development, hybrid cloud, z Analytics and IBM Canada lab director.
Hurricane season is upon us and the US is facing its seventh hurricane this season already. No matter how severe or mild, hurricanes and other national disasters are a concern for both individuals and businesses who operate in these areas.
So what happens now when we go beyond the frontiers of the data warehouse and into the world of the data lake? – the world of Hadoop, of NoSQL, the world of schema on read, of discovering the data as is? For many organizations, the holy grail is to reap the benefits of the data lake while retaining
More than 75% of C-level executives consider it a top priority to better leverage data and analytics in their decision-making. Unfortunately, less than half of individual workers say the same — a disconnect that highlights how hard it can be to make those C-level priorities a reality.
The modern data landscape demands more than one type of database. That’s IBM has rolled out JSON-document-based databases in Db2 and Cloudant, as well as partnered with select database providers to offer developer-focused database services through the IBM Compose platform.
How do baseball scouts use machine learning and AI to predict player performance? Ari Kaplan, Principal at Aginity, and David Kearns, Offering Manager, IBM Analytics Ecosystem, join us to talk about the recent merge of H20.ai and IBM. They also discuss how baseball decisions are made using
There’s a lot to love about open-source technology. Based on the idea that a community of people can iterate on and improve something better than a single person, team, or even company, open-source promises continuous innovation and community support.