How mainframes put muscle behind autonomous data maintenance software

Before autonomous data correction software met the mainframe, a day in my life as a DBA looked like this:

2 a.m. – Diagnose a critical maintenance utility failure for a panicked night operator, re-submit the REORG job, and head back to bed.
8 a.m. – Leverage a database tool to pull pertinent data for an emergency report on an internal customer’s sales region.
9 a.m. – Use various database tools and review performance-related data to improve data access for developers alarmed their application performance is slowly degrading.
12 p.m. – As lunch approaches, identify where I can save data for a scheduled backup, having noticed unforeseen space problems, and successfully capture my backup.

There I was, a highly trained computer professional, troubleshooting random bugs and issues, sometimes in the wee hours of morning.

The world changed for DBAs like me when database tools came on the market. Rudimentary at first, the past 20 years have seen such software blossom into autonomous tools that can adapt and intervene on a DBA’s behalf to address any event before it becomes a problem.

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