As it is said that “Data is a new fuel for organizations to generate profit and revenue”. So, the considered source (data source) for truth to get business insight is actually a source of truth and there is no discrepancy in the data.
As Enterprise decisions depends on the data and it plays a very important role thus it needs to go through all the quality and reliability check, also integrity of the data is constantly maintained.
“Data Governance is mechanism of establishing a system over the organizations data storage, which enforces policies and procedures for data accuracy, reliability, compliance integrity, and security”
Benefits of Data Governance:
An effective data governance strategy provides many benefits to an organization, including:
· A reliable and consistence data source
· Single version of truth: Data is monitored and maintained with data quality policies
· Cost saving: can improve customer service by knowing the accurate status of ongoing activity, inventory, and manpower availability.
· A common understanding of data: Data governance provides a consistent view of, and common terminology for, data, while individual business units retain appropriate flexibility.
· Improved data quality: Data governance creates a plan that ensures data accuracy, completeness, and consistency.
· Data map —business can trace back to actual source of data and data governance makes data assets useable and easier to connect with business outcomes.
· A 360-degree view of each customer and other business entities
· Consistent compliance —EU General Data Protection Regulation (GDPR), the US HIPAA (Health Insurance Portability and Accountability Act), and industry requirements such as PCI DSS (Payment Card Industry Data Security Standards) are followed
· Improved data management — Data governance improves practices and management process beyond traditional data and technology areas — including areas such as legal, security, and compliance — are addressed consistently.
Frame work for data governance: a data governance framework is model and strategy to lays down the data governance system and the framework implies the rules, activities, responsibilities, procedures, and processes that define how those data flows are managed and controlled. Also, who, what and how data will be accessed by other system/applications.
The following should be considered while designing a Framework:
· Data scope: master, transactional, operational, analytical, Big Data, and so on.
· Organizational structure: roles and responsibilities between accountable owner, head of data, IT, business team, and executive sponsor.
· Data standards and policies: guideposts that outline what you’re managing and governing and to what outcome.
· Oversight and metrics: parameters for measuring strategy execution and success.
A data governance framework is continuous process and an organization would be using it as daily life routine and it must continually monitor and re-evaluated in light of the changing volume, types, and character of data that your organization handles.
