Data governance is a framework including people, process and policies, which every organization needs to build secure, reliable and business trustworthy data assets. It improves business productivity and operations.
Governance is the key to build data driven organization. It enables organization to define data elements consistently so all data actors know what they mean in their business domain. Without consistent definitions wrong business
decisions could be taken costing organization millions of dollars.
For enterprise data governance a separate group should be created, which primarily focuses on governance because it is a lengthy and on going process. The group consists of data governance officer/head and data stewards, business side
of data owners etc.
Data governance deals with processes, users and data assets to deliver reliable data to business governance policies and processes need to be implemented as a workflow.
Where data related changes are appropriately approved by data owners, processes gets defined and approved by data councils.
Data Governance process includes data ingestion, quality validation, cleansing and standardization to make consistent data for business use. Clean and reliable data is the essential foundation of any data applications. Data quality issues could cause major issues in a company. Invalid execute dashboard can lead to wrong business decisions, data issues will cause wrong business rules results, invalid output from data models etc. Clean data will increase trust, productivity and reduce costs.
Data discovery allows identification of critical, sensitive data elements. Governance based security policies can restrict critical data elements access and masking.
Data dictionary provides detailed information about data elements and business domain specific meanings. It enables business users to understand and use the data elements appropriately in their decision making and reports.
Data dictionary establishes clear communication between IT and business so right allowable values and types can be present in data.
Trust in clean data enables business users to make confident decisions. To provide trust tracing from where the final data came from is very important.
Lineage feature allows visual tracing of data sets with clear business friendly data definitions.
Monitoring people, processes and policies is essential to maintain good enterprise governance. InsightLake governance solution provides dashboards to see how different data sets are getting utilized, changed, and accessed.
Centralized view and roll up analytics at client, system, business units and division enables clear ownership and usage.
Governance solution provides management of enterprise data ownership structure.
Setting up data governance is a very long process, which requires all business units to come together and make co-ordinated decisions. It requires organizations to spend time and money in focused and dedicated way.
There are many challenges:
Data governance should be done in stages to achieve success.