Although data governance and data management may often go hand in hand, data governance primarily concerns assessing, using, managing, monitoring, improving, maintaining and protecting valuable information or data of an organization or a company. It also encompasses the process, people and the information technology needed for creating an appropriate handling system of the organization’s data across its business activity that include achieving targets such as

• Increasing the consistency and buoyancy in making decisions
• Decreasing the regulatory fine hazards
• Exploiting the income generating potential of relevant data
• Ameliorating data security
• Delegating accountability in information eminence

Data governance however, aims at improving the quality of data by way of establishing a team consisting of the leadership, business managers and data stewards who are responsible for the accuracy, consistency and totality of the available data. The team so assigned often employs some form of tactic for tracking and improving quality of data like the Six Sigma as also tools for data mapping, cleansing, profiling and also monitoring data.

Initiatives in data governance are also aimed to achieve several objectives that include transparency for the external and internal customers of a company as is done in supply chain management, complying the relevant regulatory by-laws, improving operations during corporate mergers, as also aiding the competence of knowledge employees by eradicating confusion and error factors. Instances of several data governance steps being inspired by endeavors in the past to improve information quality are not rare.

As far as implementation of data governance initiatives are concerned, they often vary in range and also in origin. A mandate may sometime arise to begin an enterprise broad enough, while another may arise to start a pilot project or several projects that are restricted in objective and scope. These are usually aimed to resolve the present issues or simply for demonstrating value. Also, often an initiative may originate at lower down the rung and would be for setting up through a limited scope for demonstrating value to the potential sponsors who are higher in the organization.

Data governance usually needs tools though it was declared at the Data Governance Conference held in Orlando, Florida in December 2006 that it mostly communication on which the topic resides. Taking this clue, vendors try to position their products as data governing tools, focusing areas of various data governing initiatives. But sad to say, they are usually found inappropriate while some of them marked governance tools actually address governance needs.

Also, in most companies, there are some areas in reference data which proves crucial for the main business. Take for example financial management where the identification of investment opportunities is of great importance. However, closer examination often reveals that the data is not the same in quality and usage all through the organization. Ingrained definitions that are specific to individual businesses complicate the issue further. Then there are political pressures and internal lack of trust that often changing the color of the given data. Data governance in such scenarios may take the form of MDM or Master Data Management program.

Sometimes, large multi-national companies utilize shared data among its white collar executives in order to market a much awaited product or services before the due date. This obviously causes strain in their existing data governance system. But how one of the world pharmaceutical leaders, Pfizer had solved the problem is given here as a case-study.

Since data governance is proving more and more popular with most medium and large organizations in the United States, this treatise will prove rather inactive if some of the major data governance organizations are not revealed here. The IBM Data Governance Council is a body that consists of companies, corporations, Technology Solution providers and institutions who have the related objective to create quality control and consistency in governance for companies to better protect their crucial data.

The DGS-COP or the Data Governance & Stewardship Community of Practice is a vender-neutral group that is open to practitioners, stakeholders, academics, consultants and vendors. It provides many helpful implements to its members that include case-studies, dashboards, maturity models and online events.

People also obtain valuable help through attending Data Governance Conferences that are held in the US as well as in Europe every year where various institutions and companies show case their models for the benefit of attendees.

Data is not anymore the simple business information of a few years back. It can mean a lot more today in this complicates market place. And that is why terms such as data governance have evolved – and we can only expect that its importance will be on the rise in the years to come.