Trends
10 principles of data governance
Data governance principles help to improve the efficiency of an organisation’s management and use of its data assets.
Headline
Data governance principles help to improve the efficiency of an organisation’s management and use of its data assets.
Context
Data has become a core asset and a source of competitive advantage for enterprises. Effective data governance is like the nervous system of an enterprise, ensuring that data flows in an orderly manner, is of reliable quality, and is secure and controllable, thus empowering business decisions, driving innovation, and improving operational efficiency. Also read: Google Cloud and NetApp introduce enhanced data storage
Evidence
Pending intelligence enrichment.
Analysis
Data governance is not an isolated technical behaviour but should be closely integrated with business. The data governance team should maintain close cooperation with business departments to understand business processes, application scenarios and decision-making needs, and ensure that the data governance strategy is highly compatible with the business strategy. The goal of data governance is to enhance the value contribution of data to the business, so every governance initiative should be oriented towards improving business performance, optimising customer experience and facilitating strategic decision-making. Treating data as an enterprise asset is a prerequisite for effective governance. This means that enterprises need to establish a data asset management framework, quantify the value of data through data asset catalogues and valuation models, allocate resources appropriately, and ensure that data is properly stored, efficiently utilized, and continuously added value. The perspective of data asset-based prompts enterprises to look at data governance from the perspective of return on investment, making it a strategic lever to drive business growth.
Key Points
- Data governance must align closely with business goals, treating data as a valuable asset and ensuring comprehensive lifecycle management. This integration optimizes resource allocation and enhances data integrity, driving business growth and performance.
- Enterprises must prioritize data quality, compliance, security, standardization, and integration to ensure accurate, secure, and standardized data for informed decision-making and organizational growth.
- Enterprises should establish collaborative governance structures, leverage technology, prioritize continuous improvement, and foster a data-driven culture to optimize data governance practices.
Actions
Pending intelligence enrichment.
