Data Governance must for Trusted Information

Data GovernanceData governance is a set of processes that ensures that important data assets are formally managed throughout the enterprise. Data governance ensures that data can be trusted and that people can be made accountable for any adverse event that happens because of low data quality. It is about putting people in charge of fixing and preventing issues with data so that the enterprise can become more efficient. Data governance also describes an evolutionary process for a company, altering the company’s way of thinking and setting up the processes to handle information so that it may be utilized by the entire organization. It’s about using technology when necessary in many forms to help aid the process. When companies desire, or are required, to gain control of their data, they empower their people, set up processes and get help from technology to do it.

Each organization can define their goals related to data governance. Some basic common goals are:


  1. Increasing consistency and confidence in decision making
  2. Maximizing the income generation potential of data
  3. Designating accountability for information quality
  4. Improving data security
  5. Decreasing the risk of regulatory fines
  6. Acknowledge and hold all gains
  7. Enable better planning by supervisory staff
  8. Minimizing or eliminating re-work
  9. Optimize staff effectiveness
  10. Establish process performance baselines to enable improvement efforts


Governing data today is an organizational responsibility, and there is clearly a need for common solutions and governance models to protect and share data on different levels across the organization. Moreover, the complexity extends beyond structured customer data. Organizations are concerned about governing access to many types of data including unstructured content, trade secrets, financial data, patient information, video, audio, etc. Beyond new methods to protect data, effective data governance can play a vital role in driving new business opportunities and retaining existing customers by improving overall data quality and business intelligence. Companies seeking to get a true handle on their data must go beyond simply protecting it.


Steps to a successful data governance process are as follows:


a)    Select right people for right job: The first step to successful data governance is to select/find an individual who carries the delegated authority and making the person accountable to carry out all the required activities. Team need to be selected appropriately. All stakeholders need to be brought together with a consensus about the activities to be carried out.


b)   Take a note of the situation: Organization processes and practices need to be reviewed. It helps benchmark where the organization’s data-governance program is today and delivers a road map to determine where it will be tomorrow.

c)    Develop a data-governance strategy: After assessment about company’s current level of data governance, data governance team should lay a plan for next few years on how the company will increase its level of data governance. Plan designed should be relevant and realistic in terms of goals to be achieved within a stipulated deadline and also set key performance indicators to track progress.

d)    Calculate value of data: If you want to calculate the value of your data, build an internal marketplace for data based on user entitlements and the utility of IT services. When everyone in an organization is paying for IT services and data directly, the value of data is part of the business P&L.

e)   Calculate probability of risk: Past history about usage of data can help determine how data might be compromised and disclosed in the future. Every organization has records of transaction which are unused. Collecting it, relating its meaning and studying loss trends over time can help any organization transform risk management into a fact-based, business intelligence method for analyzing past events, forecasting future losses and changing current policy requirements to improve your mitigation strategies.


f)     Monitor the process: The goals which have been set, the task which has been laid down and work that needs to be done has to be monitored on continuous basis. Data governance is largely about organizational behavior. Organizations change every day, and therefore their data, its value and risk also shift rapidly. Unfortunately, most organizations assess themselves only once a year. Data governance is much more than simple security, compliance or risk management. It’s all of them and more. It’s about how an organization uses data to benefit and protect itself.