Five Minute Briefing - Information Management
July 22, 2020
Five Minute Briefing - Information Management: July 22, 2020. A concise weekly report with key product news, market research and insight for data management professionals and IT executives.
News Flashes
EY (formerly known as Ernst & Young) and IBM have announced an enhanced, global multi-year alliance to help organizations accelerate digital transformation and improve client outcomes, including leveraging the hybrid cloud capabilities of Red Hat OpenShift, as well as IBM Watson, IBM Blockchain, and IBM's 5G and edge technologies. "Expanding this global alliance bolsters our ability to bring our hybrid cloud and AI capabilities to clients," said Arvind Krishna, IBM CEO.
MemSQL, the database of now for operational analytics and cloud-native applications, is forging a new partnership with Latin America Business Consulting (LATBC) as the exclusive reseller for MemSQL in Mexico, Central America, and the Caribbean.
ScaleOut Software is releasing ScaleOut StateServer Pro, adding integrated data analytics to the company's ScaleOut StateServer in-memory data grid (IMDG) and distributed cache. ScaleOut StateServer Pro builds on its powerful foundation and takes in-memory data storage and distributed caching to the next level with integrated, data-parallel analytics.
Siemens and SAP are forming a partnership that will leverage their industry expertise and bring together their complementary software solutions for product lifecycle, supply chain, and asset management. The partnership leverages expertise and technology of both companies to provide a true digital thread that helps enterprises eliminate process and information siloes, drives digitalization, and delivers a comprehensive solution for the 4th industrial revolution (Industry 4.0).
At Data Summit Connect 2020, Elliott Ning, cloud advisor, Google, discussed how AI has replaced business intelligence as the key driver of strategic decision-making. There are four categories of analytics use case, Ning explained. First is descriptive analytics, like aggregating business data during a period of time. For example, getting information about total revenue from last month, last quarter, or last year.