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.
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
On the second episode of Data Decoded, Seth Dobrin, VP & CDO of IBM Analytics discusses his role as a Chief Data Officer at IBM and the latest IBM Analytics announcements from Think 2018, from IBM Cloud Private for Data to launch of the Data Science Elite Team.
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.
Managing enterprise information has always been a good idea, however with the potential for looming penalties from the General Data Protection Regulation (GDPR) non-compliance, companies are waking up and some organizations are even seeing GDPR as an opportunity to establish strengthened
Although there are many new and emerging classes of data integration, quality and governance software tools available in the market, many large organizations are coming to the conclusion that they're best served by a single unified enterprise data integration, quality and governance platform that
In the connected world of today’s digital economy, apps, IoT devices, vehicles, appliances and servers are generating endless stream of event data. The stream of events describes what is happening over time and offers the opportunity to track and analyze things as they happen.
Recently, I had the honor of speaking with a number of the world’s most influential thought-leaders in the fields of data science, data analytics, machine learning and digital transformation. This group of prominent data technologists was more than happy to answer a wide variety of question on