According to Grand View Research, the global multi-cloud management market is expected to grow at an annual growth rate of 27.5% from 2022 to 2030.
With a 92% cloud adoption rate across industries, it’s clear that the future of enterprise analytics is in the cloud. Organizations seek to create, consume, and control their data, and information assets to gain valuable insights from it. Data governance requires a system and a strategy. It’s crucial to have a solid framework of the people, processes, and technologies to maintain compliance with regulations, and mitigate risks.
Let’s explore the key steps for building an effective data governance strategy.
Key Steps for Future-proofing Data Governance
A good governance strategy must mitigate the risk related to poor data quality, minimize the compliance risk, encourage data utilization, and demonstrate success through short-term goals. We have listed a few frameworks for future-proofing data governance strategies for businesses.
Here are some frameworks that companies must undertake.
Eliminate Redundant Data: The best way to govern every bit of data is to ensure it is trustworthy, consistent, and not redundant.
Data virtualization is an approach that prevents the creation of duplicate data, analytical data marts, or additional data repositories allowing virtual data creation on top of existing data repositories.
Centralize Data Access Control: Centralized access control allows access to all applications, websites and other computing systems from a single profile anytime, anywhere. Formulating a logical data fabric with data virtualization would centralize and simplify the data access control.
Decoupling Data Security from Data Repository: Modern data security policies are complex and need real-time controls. Decoupling the security measures from repositories and defining them across all BI tools and repositories would map the policies across all data sources.
The practices mentioned above are a great way to start data governance in a company. Implementing easy and simple steps of setting accountability will do great work with agreeable objectives.
To know more strategic frameworks, read our blog.
Data Governance is the Key Element of a Data Product
Data must be treated like a product to ensure accessibility, compliance, and reliability. Only the best technologies and tactics will not be enough.
Businesses find it difficult to manage data governance. They must first list all parameters and determine who is in charge of them. Data assets must therefore be decentralized in order to disperse data ownership. Organizations must design ownership & accountability, clear, quantifiable measurements, and data quality statistics in order to reduce the risks associated with data governance.
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