Data governance is best if the organizations have a steering committee, a governing body, a group of data stewards and a governance team of course. It is teamwork and all these elements work together to create policies and standards for governing data, implementing it and enforcing the procedures.
Why Data Governance
Data governance helps data consistency in the systems like the names of customers should be listed differently in customer service systems, logistics and sales. If the data governance is not effective, data integration complications can be suffered and data integrity issues can happen. All these may lead to non-identified data errors and hence data fixing can never be possible.
It is important to note that poor data governance may hamper the regulatory compliance initiatives and as an aftermath the organizations may face problems related to complying with the latest data privacy and protection laws.
Data Governance Benefits, Goals
Breaking down the data silos is the primary goal of data governance. The silos are built when separate transaction processing systems are used without equipping these with centralized coordination or without having any enterprise data architecture. The focus is always to harmonize the data in the mainstream system by using a collaborative process.
The second key goal of data governance is to ensure the data is used properly, without error and simultaneously blocking any misuse of it. All these can be achieved by accomplishing uniform data use policies and also have a procedure for monitoring the usage of data.
Data Governance and Responsibility
Often, the chief data officer (CDO) is responsible for looking after the data governance program in organizations. He is responsible for the success or failure of the data governance. His key role includes staffing and funding the program, securing approval, leading the entire setup, monitoring the data governance progress and simultaneously advocating internally.
In some cases like Gartner master data management, the director of enterprise data management is responsible for the success and failure of the data governance. Some organizations even have data governance manager to lead the program and his is liable to the outcome. If the two such designations are missing, the organizations have a setup of data governance office and it coordinates with the program.
Organizations dealing in data should have a proper data governance system at work. Poor data governance means errors, misuse and many more that may impact adversely. This is the reason it is always suggested to master data management by having a proper strategy and policy related to data governance to ensure the data is used properly and uniformly.