The fusing of analytics with leading technologies can unlock significant business value and bring new transformation opportunities for enterprise companies. In order to be successful, analytics-based initiatives such as AI and the Internet of Things (IoT) need massive amounts of big data—and also
In a previous blog, I explained how data science capabilities, massive parallel processing (MPP)
and usability improvements in data warehouse appliances can help the bottom line—and why old-fashioned architectures might not cut it. But what does that look like in practice?
Research firm Quark +
It’s no surprise: most companies working with stream data today say they are planning to make changes to drive greater value. Advancements in machine learning (ML) and very-high-speed data persistence for real-time analytics are reshaping strategies and architectures. In addition, 88 percent of
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