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Data Governance: The role it plays in managing an organisation's data

In previous weeks here on the Intergen blog, I’ve looked closely at two data-related topics Data Quality and Master Data Management. In today’s final wrap-up, I take a high level look at Data Governance and the role it plays in managing an organisation’s data.

Data Governance is about both business and IT leaders making strategic decisions regarding an enterprise’s data assets and the information environment to ensure it meets the needs of the enterprise. Meeting these needs can cover a number of different areas; needs for analysis, needs for operations, as well as the needs of each individual department such as HR, sales, production and so forth.  

Data Governance, as defined by the Data Management Association (DAMA), is a framework for managing all the data within an organisation and covers all aspects of data. Figure 3 shows the DAMA Data Governance Framework. Implementing a full data governance program covers all aspects of data regardless of where it is found within an organisation.

Data Management Association Data Governance Framework

Data Management Association (DAMA) Data Governance Framework

 

Fully implemented, a data governance programme may consist of a data governance board and data stewards or data stewardship committees. Data stewardship is the responsibility, accountability, and authority of a data steward over a data subject area across the enterprise, overseeing its definition, quality, security, and effective use

It is important to recognise that data governance is not an IT function. IT is a member of the data governance board but any effective data governance program requires executive sponsorship and business involvement.

To get the most out of your data warehouse and business intelligence implementation, a Data Governance Maturity Assessment should be performed. As every organisation differs in their business, their systems, management style and so forth, performing the Data Governance Maturity Assessment will help in designing both the short and long-term goals for implementing a Data Governance program that is tailored for the organisation.

Why do a Data Governance Maturity Assessment? How an organisation uses its data can be the difference between average performance and competitive advantage. Implementing a BI solution is important to turn the data in the organisation into useable, actionable information. However, if the data is inconsistent or incorrect, the information generated can lead to incorrect decisions. 

The Assessement will help in creating a data strategy that focuses on accurate, consistent and transparent data while fostering an organisational culture that recognises data as an asset. A BI solution that uses inaccurate data as its source can be worse than having no BI due to potential problems with the information provided.

The Data Governance Assessment looks at a number of factors:

  • Privacy and Compliance. Depending on the organisation, there may be specific privacy and compliance rules that must be part of a data governance program. For example, financial and medical institutions often must have a higher level of cutomer privacy when compared to other organisations. Any governance program must ensure the organisation is in compliance with all the regulations pertinent to them.
  • Data Management. Is there a centralised program for managing data or is each data source treated individually, more of a siloed approach? What is the best approach for the organisation? This is something that may change over time.
  • Data Quality. What processes are in place, or can be put in place, to address data quality issues?
  • Business Alignment. How does data management and integration align with the business? How can the data be used to help the disparate groups within the organisation to align their individual goals and activities with overall business goals?
  • Information Architecture. How is data stored and shared within the organisation? Are there multiple data platforms and applications? Different data sources? How are each of the systems managed? How is data merged or exchanged between systems?
  • Business Intelligence. To what degree has BI been implemented in the organisation? Who uses it and how?  What key decisions are being made and what are the chances that the data being used has quality issues? Is the data being obtained directly from source systems or through a data mart or data warehouse? Is the business intelligence all pre-defined dashboards, reports and metrics or is there a BI self-service component?

An effective data management strategy enables an organisation to adapt quickly in a dynamic business environment. A great quote in regard to data management comes from business guru Tom Peters who said “Organisations that do not understand the overwhelming importance of managing data and information as tangible assets in the new economy will not survive”.

One last word on Data Governance. Not every company will implement every aspect of the Data Governance Framework. The Data Governance Maturity Assessment will also help determine which aspects make the most sense for your business both in the short-term and the long-term and it is possible that you may determine that the cost-benefit ratio for some aspects will deter you from addressing those areas. That is fine, don’t feel bad. Every business is different and so each Data Governance program will differ as well.

I hope you have found this series useful and is of use in evaluating the quality of data in your organisation.  May your data be good and your analysis insightful. If you’d like to talk in detail about any of the points raised over the last three blogs, or talk about your organisation’s data management processes, please get in touch: mark.worthen@intergen.co.nz.

Posted by: Mark Worthen, Senior Consultant, Enterprise Applications | 11 December 2012

Tags: Business Intelligence, BI, Data, Data Accuracy, Data Governance, Data Quality, Master Data Management, Data Governance Assessment, Data Governance Framework


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