There are numerous challenges to working with distributed data. How do we secure, analyze and govern data in a hybrid cloud world? In this podcast, Michael Factor from IBM Research describes what a hybrid data fabric is and how it helps companies gain value from data in distributed locations.
Michael Factor's bio.
Dr Factor is an IBM Fellow with a focus on cloud data, storage and systems. He has a B.Sc., Valedictorian (1984) in Computer Science from Union College, Schenectady, NY. M.Sc. (1988), M.Phil. (1989) and Ph.D. (1990) in Computer Science from Yale University. Since graduating, Dr. Factor has worked at the IBM Research — Haifa.
His current main focus area is hybyrd cloud data. Among his responsiblities is as a global lead for all work on Hybrid Data form IBM Research. In this role, he and the global team are defining future directions to ensure 1) it is easy to get the right data for a task, 2) that data is always used in a secure and governed fashion and 3) that IBM has high-performance, secure, highly-functional and cost efficient data stores and processing engines. In addition, he serves as the main focal point in moving IBM Research innovations from the Lab into the IBM public cloud where his team has contributed to services such as IBM Cloud Object Storage, IBM SQL Query Service, and various Spark related services. Beyond his Research efforts, he also works closely with both the IBM Public Cloud and the IBM Data and AI team to provide guidance and expertise on directions such as serverless computation, data lakes and future enhancements to object storage.
You can follow Michael's research here.
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