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.
On this week's episode, John J Thomas, Distinguished Engineer and Director for IBM Analytics, and Steve Moore, Senior Content Designer and Story Strategist, join us to talk about data science and how your business can best weave the skills of a data scientist into their decisions. Learn how to
Purchasing options outside of the office are diverse and varied depending on what people want to buy, where and when they buy it, and what they need it for. While shoppers might have personal preferences, they don't limit ourselves to one retailer for all purchasing decisions. So why do that in a
By 2025, there will be 180 trillion gigabytes of data in the world, compared to only 10 trillion gigabytes in 2015. Of this, 90 percent will be unstructured, which is why many organizations are adopting open source data lake technologies such as Apache Hadoop to handle this expanding volume and
Join us 27 February at 1 PM ET for "Machine Learning Everywhere: Build Your Ladder to AI." Visit the event landing page to learn more about the event and register for a calendar reminder: ibm.com/mleverywhere
Readers of the IBM Big Data & Analytics Hub were hungry for knowledge this year. They voraciously read blog posts about incorporating machine learning, choosing the best possible data model, determining how to make the most of data science skills, working with open source frameworks and more.
The data lake may be all about Apache Hadoop, but integrating operational data can be a challenge. Learn how to deliver real-time feeds of transactional data from mainframes and distributed environments directly into Hadoop clusters and make constantly changing data more available.