IBM Needs a Holistic Approach to Governing Big and Small Data on System z

IBM System z is the premier mainframe platform in the market today. Many of the largest enterprises in the world rely on System z for their business critical operations. At the same time, these organizations are also maturing their data governance and big data initiatives. However, in many cases, these organizations have not tied their data governance and big data initiatives back to the mainframe where most of their mission-critical data currently resides.

The light bulb went off for me when I was talking to the manager of data governance at a financial services institution. We were establishing information policies around email addresses. They had to quantify the number of missing email addresses but that data was on the mainframe. They wanted to set policies around customer duplicates but their customer information file was on the mainframe. Their CIO wanted to reduce storage costs. Most of that data was on the mainframe. Their Chief Information Security Officer (CISO) needed to set policies, but most of the data was (you guessed it) on the mainframe.

Now, let’s talk about big data. Yes, there’s lots of hype but I fully expect that some of those vast oceans of data will land on System z. An insurer recently mentioned that they were looking at a telematics program that placed sensors on automobiles. They also mentioned that this treasure trove of sensor data (big data) would probably end up in the System z environment.

IBM actually has a broad portfolio of tools for governing big and small data on System z. I have listed a few below:

  • Data Profiling – Assessing the current state of the data is often the first step in a data governance program. IBM InfoSphere Information Analyzer offers data profiling capabilities on System z.
  • Data Discovery – A large financial institution had thousands of VSAM files. They found that Social Security Numbers were hidden in a field called EMP_NUM. A data discovery tool like IBM InfoSphere Discovery helped them discover hidden sensitive data on the mainframe.
  • Business Glossary – IBM InfoSphere Business Glossary for Linux on System z enables large mainframe shops to deploy their business glossaries in a System z environment.
  • Data Archiving – I know of at least one large institution that had data from the 1950’s still sitting on the mainframe. IBM InfoSphere Optim Data Growth helped rationalize their MIPS costs by moving older data to less expensive storage.
  • Database Monitoring – Many large financial institutions want to monitor access by privileged users like DBAs to sensitive data on the mainframe. IBM InfoSphere Guardium now offers S-TAP support for IMS, VSAM and DB2 on z/OS.
  • Big Data – The IBM DB2 Analytics Accelerator for z/OS allows companies to accelerate analytical queries by leveraging the power of a Netezza appliance.

I am not suggesting that every data governance program needs to now focus on System z. However, there are many large IBM mainframe shops that are building out their data governance and big data programs. I do believe that these organizations would benefit from a better alignment between System z and their data governance and big data initiatives.

About sunilsoares

Data Governance Practitioner
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