IBM this week unveiled their new data science and machine learning platform, displaying their aggressive push to speed up artificial intelligence (AI) adoption at organizations worldwide.
The new Cloud Private for Data platform is aimed at bridging the gap between AI technologies and the information architectures required to analyze the data that powers these systems. This latest offering uses microservices to form an integrated environment for data science and application development.
Leveraging a fast in-memory database for analyzing large swaths of data, IBM reports that the new system can process one million events per second, according to internal tests run in February of 2018. The new platform is designed to help uncover previously unobtainable insights from core business data and event-driven applications, such as IoT sensors, online commerce, mobile devices, and more.
Currently using the IBM Cloud Private, a private cloud platform launched late last year, Cloud Private for Data is an application layer deployed on the Kubernetes open-source container software. Essentially, the new solution provides a data infrastructure layer for AI behind the firewall.
IBM reports that Cloud Private for Data will ultimately run on all clouds and within industry-specific solutions for financial services, healthcare, manufacturing, etc.
With this announcement, Rob Thomas, General Manager of IBM Analytics, said they were bringing "the AI destination closer" and giving "access to powerful machine learning and data science technologies [to] turn data into game-changing insight."
The Cloud Private Data solution also includes key capabilities from Data Science Experience, Information Analyzer, Information Governance Catalogue, Data Stage, Db2, and Db2 Warehouse.