What Does Data Governance Mean?
Data governance serves as an umbrella that covers all data management policies and procedures. In terms of definition, it is the principled methodology we follow to organize and structure data within a company, starting from acquisition to disposal. With it, we define the ownership of data and the policies that drive data retention and security within an organization.
The Need for Designing Data Governance That Delivers Value
Ineffective data governance services plague most organizations across the globe as the higher management fails to recognize the value-adding potential of this approach. Any company that doesn't implement proper data governance & analytics policies faces issues with compromised analytics and a lack of reliable information. As a result, they largely miss out on opportunities that optimize operations and open new revenue streams. With that in hindsight, here are some of the major benefits offered by a data governance approach for value:
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It helps make more streamlined decisions
Users within the organization need access to data to provide service to the customers and further improve the product. Data governance helps deliver it.
Greater cost controls
We need data to manage our resources more effectively. We can eliminate duplicate data caused by information silos and prevent over-purchasing with data governance.
Regulations have gotten stringent of late, making way for increasingly robust data governance models that help avoid risks associated with non-compliance.
Data governance ensures that both external and internal data policies are compliant and auditable. This furthers the trust developed with customers and stakeholders to ensure that their sensitive information is protected.
Intersecting Data Analytics and Data Governance
The era of big data hasn't been easy to accept for most, and companies haven't had much of an option other than taking a reactionary approach to data management. As a result, innumerable businesses are reeling under data exhaustion.
To alleviate problems such as this, we must find a way to make the best of seemingly disparate data governance and data analytics software and tools. We say this because while data governance serves as the foundation for a larger data management program, it's only through an analytics platform that an organization can boost their governance efforts.
Analytics-driven data governance
Data governance enables organizations to leverage their data as an enterprise asset. Therefore, it is crucial to understand similar data assets across an enterprise, especially when its key components include business glossaries, data dictionaries, and metadata management. With the data governance paradigm, we assign data owners and stewards to bring accountability into the picture and thus ensure data quality.
When we introduce analytics into the scene, machine learning algorithms can help improve the quality of data across the enterprise and improve themselves as it goes forward. For example, with data governance and AI leveraged together, organizations can ensure increased data utilization for analysis and make the data more reliable. Moreover, with analytics, organizations can proactively pinpoint areas where they may violate certain regulations, like the General Data Protection Regulation (GDPR).