IBM Db2 - The Ultimate Database for Cloud, Analytics & Mobile
Db2 AI for z/OS Launch webcast
Date: 1st June 2021 Time: 11:00AM – 12:15PM
IBM Extends Industry-Leading Enterprise AI Announcing Watson Machine Learning for z/OS 2.3 and Db2 AI for z/OS 1.4
Catherine Wu, Head of Development, Data and AI - IBM China Lab, will kick off the discussion and share the latest enhancements around IBM Watson Machine Learning for z/OS.
IBM Watson Machine Learning for z/OS is the AI and machine learning platform for IBM Z. You can train AI models in any framework, on any platform, including IBM Cloud Pak for Data, then readily deploy those models on IBM Z to score/inference in-transaction, in-real time.
Catherine will showcase the latest Watson Machine Learning for z/OS enhancements and a new On-line Scoring Community Edition – a no-cost, light weight trial offer providing organizations an opportunity to try the in-transaction inferencing approach on IBM Z. Watson Machine Learning for z/OS offers real-world machine learning for your real-world transactional applications.
Db2 AI for z/OS
Erika Adkins, Db2 for z/OS Program Director, IBM Silicon Valley Lab will follow Catherine and share the latest enhancements of Db2 AI for z/OS. IBM continues to infuse AI into Db2 for z/OS, with this new release, Db2 for z/OS will operate smarter and more efficiently, helping to improve Db2 application performance with deeper integration between system assessment and SQL optimization features which can be augmented by ISV data. This can help reduce the time required to discover application performance problems, and identify and apply the necessary tuning. You will learn about exciting enhancements in the areas of:
Example IT and Business Use Cases
To wrap up, Eberhard Hechler will share some customer experiences spotlighting the value of Db2 AI for z/OS and Watson Machine Learning for z/OS. He will provide examples of Db2 for z/OS specific IT-related use cases such as SQL optimization and DRDA traffic management. Eberhard will also highlight some business related use cases for in-transaction scoring such as fraud detection, loan approval and crime prediction.