Data governance is the management of organizations’ data availability, usability, integrity, security, and privacy. According to Gartner, Data governance is the specification of decision rights and a framework for accountability to assure acceptable behavior in the value, generation, consumption, and control of data and analytics.
Why Do Organizations Need It?
It ensures that data is consistent, reliable, and trustworthy, which helps to avoid inconsistencies or errors. It helps in regulatory compliance ensuring that firms comply with all levels of regulatory obligations consistently. This is key to minimizing operating costs and eliminating hazards.
Data Governance leads to improve data quality, decrease operational cost, and more availability for stakeholders which leads to better decision making and business outcomes.
Key Pillars To Data Governance:
Consider the following when looking for a modern data governance tool to support your data governance framework
- Stewardship: Consider using a data governance platform with data stewardship capabilities to see the impact. Your workforce should be able to comprehend policies and procedures. To work effectively with the data governance council or data governance committee, they’ll need to know the stakeholders. They’ll need to connect the technical metadata to the business context to comprehend the data. And, perhaps most important of all, they’ll need a place to feel like they can trust the data.
- Data quality: Successful governance projects require accuracy, completeness, and consistency across platforms. Suppose one of the pillars of being a data-driven organization is that your team can trust the data. In that case, an integrated data quality solution may be the most critical capacity. Data quality tools provide those capabilities through parsing, data profiling, and matching functions, among other features.
- MDM: Another data management discipline that is strongly linked to data governance processes is master data management (MDM). MDM projects provide a master collection of data about customers, products, and other business entities in order to ensure that data is consistent across several systems inside an organization.
- Data governance use cases: Data governance is essential for controlling data in operational systems and BI and analytics applications supplied by data warehouses, data lakes, and data marts. It’sIt’s also a crucial part of digital transformation projects, and it can help with other corporate operations like risk management, business process management, and mergers and acquisitions. Data use continues to increase, and new technologies emerge, so data governance will likely gain more comprehensive applications
Check out DQLabs’ Agile Data Governance for more details on data governance and how your organization stands to benefit from this service. You can also signup for a 7-day free trial and request a demo.