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The increasing convergence of MDM and data governance

by Lyndsay WiseThursday, March 26, 2009

Data governance is a hot topic these days with vendors developing enhanced functionality within their product suites to support the internal processes required for a successful data governance program. The concept of data governance is simple.  The Data Governance Institute (datagovernance.com) defines it as "a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.” Basically, this involves defining and managing roles within the organization that help control data related items – whether this means assigning people to take ownership over data and the processes associated within disparate business units, or developing overall company wide initiatives that take into account more than one business area and how data interrelates. Either way, organizations are starting to look more seriously at how managing data translates into business value.

Two solution providers that have recently jumped on the bandwagon and extended their offerings to include support for data governance are Kalido and Siperian.

Kalido’s data governance is based on 3 pillars to provide overall data governance support:

  • Business rules – to ensure the validity of data and rules associated with that data including precise data definitions.
  • Governance processes – includes the assignment of roles and responsibilities to individuals involved in the process (data stewards), and the management of processes and transitions within those processes as well as the ability to handle invalid data.
  • Audit and control – Full audit trails that include historical versions, role assignment and security to limit who can approve and authorize changes to data or to new data elements.

Below provides a visual representation of Kalido Data Governance:

Siperian has recently released their Business Data Director™ that enables data stewards to manage and model data, as well as to interact directly with the hub.  Business users can create a data directory on the hub using a Web interface with workflow capabilities in real-time.  In addition, users can access data through the use of fuzzy search to broaden the traditional search capabilities.  Data stewards can also merge records automatically and preview that data as well as develop metrics to display surrounding the data.

Both of these solutions highlight the fact that, not only are data governance initiatives becoming more mature within organizations, but that organizations and solution providers alike see the benefits of putting a human element to data.  To get the most value out of data and the information it becomes, organizations are now required to manage that data and to provide processes that surround it that include the ability to create and manage definitions and how the defined data interacts with other entities within the organization.  The business value becomes more efficient business processes and the ability to centralize systems to help organizations save time and additional costs associated with inefficient business proccesses.


About the Author

Lyndsay Wise is an industry analyst for business intelligence. For over seven years, she has assisted clients in business systems analysis, software selection and implementation of enterprise applications. Lyndsay is the channel expert for BI for the Mid-Market at B-eye-Network and conducts research of leading technologies, products and vendors in business intelligence, marketing performance management, master data management, and unstructured data. She can be reached at lwise@wiseanalytics.com. And please visit Lyndsay's blog at myblog.wiseanalytics.com.


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