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VMware to Introduce 'Cloud Analytics Platform' at Online Summit

기사입력2020.11.05 10:52

Introducing VMware Tanzu-based Cloud Platform Strategy
Tanzu Greenplum 7 roadmap released for open source



VMware will host Greenplum Summit 2020 Korea online on the 19th and introduce cloud data analytics strategies based on VMware Tanzu Greenplum.
▲ VMware will hold Greenplum Summit 2020 Korea online on the 19th. [Photo = VMware]

This event will cover trends in enterprise analytics and data science and the role of cloud-based data analytics platforms in depth under the theme of ‘Cloud Analytics Platform Strategies for AI and Machine Learning.’

This event brings together decision makers, data scientists, analysts, database administrators, and developers to discuss the future of cutting-edge data analytics technologies.

At this event, VMware plans to share the following: △Strategy of VMware Tanzu Greenplum, a cloud platform that supports artificial intelligence and machine learning; △Introduction of the roadmap for Greenplum 7 based on open source PostgreSQL version 12; △Data analysis using Greenplum; and △Data analysis cases of domestic telecommunications companies and manufacturing industries utilizing the latest technologies such as cloud, AI, and machine learning.

VMware Tanzu Greenplum is a large-scale data parallel processing analytics platform based on open source PostgreSQL that provides data analytics and management tailored to diverse business requirements.

VMware Tanzu Greenplum 7, upgraded based on PostgreSQL version 12, provides higher availability by adding disaster recovery (DR) and point-in-time recovery functions similar to legacy systems to the existing Greenplum's big data parallel analysis using AI and machine learning and linkage with various data sources.

Jeon In-ho, President of VMware Korea, said, “VMware will support domestic companies to experience the same analytical and operational benefits they have experienced in public clouds in hybrid clouds by combining hybrid clouds with open source-based AI and machine learning.”
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