The key elements of successful Data Governance

[shukla7789]

Learn how to achieve successful data governance that helps organizations improve productivity and minimize costs. As the amount of data increases exponentially and becomes more indispensable to achieving business objectives, Data Governance becomes a fundamental element to increase productivity and minimize data retention costs, while ensuring better data quality and availability.

When data is used intelligently, it enables organizations to make informed decisions, intelligently address customer needs, uncover efficiencies and inefficiencies, take advantage of new opportunities, and rethink traditional business models to achieve better results. How can you leverage data to gain valuable insights?






Data governance is the top priority for 60% of data leaders nurse database by data quality ( 46% ), data science ( 40% ), self-service ( 34% ), and DataOps ( 22% ).

Source: Atlan



4 Core Capabilities to Reduce Data Discovery and Retention Efforts
A Data Governance framework enables information to be managed throughout its lifecycle so that it can support the strategic, operational, regulatory, legal, risk and environmental requirements of the organization.



Effective Data Governance: The Guide to Minimizing Errors and Achieving Data Governance Goals



Not only does this improve individual user productivity by making it easier to find information instantly, but it also reduces retention costs by filtering out data sets that are no longer needed. The 4 capabilities involved in this process are:

1. Classification and labeling: These help determine the value of data, optimize search results, and speed up data collection. Additionally, examining metadata for additional context can improve the ability to discover data quickly and easily.

Companies can incorporate classification labels into their policies to fully automate their processes. An archiving policy, for example, can automatically assign a retention period to meet regulatory requirements for data containing personally identifiable information (PII), such as addresses, health records, credit cards, passports, or phone numbers. Since policies or regulations can change over time, it is critical that data can be reclassified if the need arises.