Fast New Data Platform From IBM Helps Accelerate AI

Fast New Data Platform From IBM Helps Accelerate AI
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As companies look to embrace AI to gain competitive advantage and increase productivity, IBM unveiled a new data science and machine learning platform and an elite consulting team to help them accelerate their AI journeys.

Powered by a fast in-memory database that can ingest and analyze massive amounts of data, IBM’s new Cloud Private for Data is an integrated data science, data engineering and app building platform. Designed to help companies uncover previously unobtainable insights from their data, the platform is also designed to enable users to build and exploit event-driven applications capable of analyzing the torrents of data from things like IoT sensors, online commerce, mobile devices, and more.

Launching on the IBM Cloud Private platform, Cloud Private for Data is an application layer deployed on the Kubernetes open-source container software and can be deployed in minutes. Using microservices, it forms a truly integrated environment for data science and application development. In the future, the Cloud Private for Data will run on all clouds, as well as be available in industry-specific solutions, for financial services, healthcare, manufacturing, and more.

The Cloud Private Data solution also includes key capabilities from IBM’s Data Science Experience, Information Analyzer, Information Governance Catalogue, Data Stage, Db2 and Db2 Warehouse. The cohesive set of capabilities is designed to help Cloud Private clients quickly discover insights from their core business data, while keeping that data in a protected, controlled environment.

Separately, IBM announced the formation of the Data Science Elite Team, a new no-charge consultancy dedicated to solving clients’ real-world data science problems and to assisting them in their journey to AI. This global team of data scientists, machine learning engineers, and decision optimization engineers is dedicated to assisting clients on-site to begin helping them better understand and control their data, and to start making machine learning an integral part of their business.