What is Data Governance?
Data governance is the process that ensures data is secure, private, accurate, available, and usable. It involves the actions people must take, the processes they must follow, and the technologies that support them. It can be described as a principled approach to managing data during its life cycle – right from the time it is acquired to when it is disposed of.
Data has very quickly become a very valuable asset wherein managers and data owners need timely data to make strategic business decisions. And this brings in the aspect of compliance and the proof that data is being handled according to both internal and external guidelines.
Big data and digital transformation efforts are the primary drivers of data governance programs. With the increase in data volume from new data sources, the Internet of Things (IoT) technologies, and organizations need to consider their data management practices. Effective data governance programs are focused on improving the quality of data, while reducing data silos, and ensuring compliance with an even amount of data being distributed.
A team taking care of data governance may identify commonalities across disparate datasets. But if they want to integrate them, they would be required to partner with a data management team to define the data architecture to facilitate the integration. Data Governance also sets the policies for data access which is specific to the data or PII information.
Data Governance as a concept is more a matter of people and processes as compared to technology and tooling. In short, Data Governance sets clear standards and guidelines for data processing while helping improve the quality of the data within the organization.
Here are a few of the Benefits of Data Governance…
Data Governance can help improve data accuracy and it impacts outcomes based on that data.
Ensure security, data privacy, and compliance:
Good data governance policies provide a way to meet the demands of government regulations regarding sensitive data and privacy. Violations of the regulatory requirements can result in expensive government fines and public criticism. To avoid this, companies adopt data governance tools to set guardrails, which prevent data breaches and the misuse of data.
High-quality data: Data governance ensures data integrity and accuracy. Errors in performance metrics can steer an organization in the wrong direction but data governance tools can address potential inaccuracies.
Promote data analytics: Quality data is the foundation for advanced data analytics and initiatives. This includes business intelligence, reporting, or more complex predictive learning projects.