Tuesday, December 2, 2014

How to Capture the Signals of Data Governance Issues

Data is the life blood of Digital Organization.
Big Data means both big opportunity and big risk. What are the important data governance issues, and how to handle it effectively?

Information Management is at the risk when data is in 'bad shape'. Duplicate data, non-standardized, non-normalized data that violate business and other rules causing referential integrity problems and non qualitative data leading to bad decision making. Solution is a mixture systems, processes and policies in place ensuring strong governance and stewardship.

Information Management is inefficient when data is not searchable. Another indicator for data issue could be when lot of time is spent on searching for or finding the right data source - implying that data sets are not annotated and searchable across the organization. This is also very important aspect of data governance. 

 The other indicator of data governance is ad hoc security policies and enforcement - implying that organization wide security policies do not exist and a data steward cannot specify/enforce the policies at organization wide. Individual data sets with possibly different owners enforce their own security policies. This is also an essential aspect of data governance.

The more signals of Data governance issues could be:
(1)Duplicate data because the same company is located in multiple places - we are talking about wrong address and not on special situations. (2)Trying to sum non-additive or semi-additive fields which would provide bad data.

Data governance issues for cloudification: Cloud things that could be ignored must be addressed in the cloud. So it will require more maturity for Data Governance. The common issues include: (1) People run reports, but have no idea where the data comes from. (2) People run reports, but don't know why they're needed. (3) People run reports, but don't take action based on the output. 

It indicates the potential issues if there’s weak link between BI and data governance. The stronger link has to be drawn between the success of Business Analytics and the need for Data Governance - and vice versa. All too often, they're effectively operated as distinct disciplines, rather than as complementary and symbiotic practices. So, if your Data Governance program doesn't take account of your Business Analytics, or if your Business Analytics don't take account of Data Governance, then you've not just got a problem. You've got a potential catastrophe....

Data governance is complementary discipline for Data Management, the goal is not to focused on fixing on the handy problems or issues, but for preventing from the data breaching or other serious business incidents, the approach needs to be systematic to avoid silo, and robust, but not too rigid to stop data growth and information flow. 


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