What are Data Governance Best Practices?
Data governance is a strategic management system that defines policies, enforces decisions, and creates the processes whereby data is collected, regulated, appropriately stored, secured, analyzed, integrated, shared, accessed and used without breaching data privacy and protection laws.
An effective data governance framework in place guarantees integrity, security, transparency, availability, decreases data risk and indicates how data is generated, managed and consumed. In addition, data governance defines various layers of responsibilities in an organization. Data governance ultimately determines data architecture, data warehousing, and management alignment.
Flexibility is one of the key features of an effective data governance framework. This means it can be tailored to meet the data needs and situations of an organization and changed accordingly if required. This is because data is used for business intelligence which is dynamic and constantly evolving.
An effective data governance framework encapsulates data management, project management, and program coordination. Here are the scope and goals of each of these aspects:
- Data Management
An administrative process that involves how data is acquired, validated, stored, protected and processed to guarantee how such data is accessed, its level of reliance and how timely it is for users.
- Project Management
A practice that provides a structure for using data and making decisions based on the requirements of precise projects within a bigger project.
- Program Coordination
This is a structure and framework for tactical planning, setting goals, decision making for programs as well as for assigning responsibilities and roles. Program coordination also recognizes the major stakeholders concerned and who is permitted to grant program events and priorities.
So why is Data Governance important for business intelligence?