Data 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.
To facilitate consistent storage, reporting, analysis, and quality of data, data governance governance is being developed to ensure quality, access, and integration of data, and to maximize the effectiveness of data analytics solutions. Governance will be carried out by a council working directly with data stewards at each department/division inside the company.
In most of the companies, different departments are investigating, developing, and deploying data analytics solutions for a variety of challenges at the same time. Though data analytics are crucial to sound decision making, decision makers often struggle to obtain reliable data that is necessary to make decisions or set priorities. In order to fully realize the potential of data analytics in data-driven decision making, it is essential to have seamless and easy access to reliable data, as analysis of unreliable and inconsistent data can lead to erroneous conclusions.
For consistent reporting and analysis of data, it is crucial that the definition of data elements is common across the company. Data governance will ensure quality, access, and integration of data to maximize the effectiveness of data analytics solutions.
Data governance ensures that important data assets are formally managed
While some data governance activities would continue at the institutional level, a data governance program at the systemwide level can help guide governance, optimize data analytics and refine approaches and optimize analytics solutions.
Data governance defines roles and accountability for all owners, stewards and data custodians as part of the mechanism for:
- improving data quality through consistent data definition (such as a common definition of “active student” or “concurrent enrollment”), which improves the accuracy of analytics solutions,
- enabling seamless and easy data access for legitimate use,
- improving the security and privacy of data through proper data classification,
- addressing data duplication issues and data silos and facilitates transparency through data-sharing across departments, units, and institutions, and
- improving compliance and mitigates risks
- Involvement of data stewards (such as the registrar and controller), is key to creating and maintaining common data dictionaries so that data elements like “active students” are defined consistently across business units and campuses.
- A data governance program, governed by a council would enable a number of highly beneficial business practices:
- develop, implement, maintain, and help enforce systemwide data management policies, standards, guidelines, and operating procedures to enhance institutional data with consistent definitions and classifications;
- advise on data warehousing, business intelligence/analytics, master data management, data dictionary, and metadata management;
- establish specific, measurable, mission-centric goals and KPIs to periodically evaluate and improve the effectiveness of the goals; and
- develop and implement ideas for enhancing awareness of and training for data governance activities throughout the system.
For key aspects of this initiative to be successful, a Data Governance Council must established. Members of this council should represent leaders of various functional areas of the company in addition to their counterparts at System Administration.