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Building a Robust Data Governance Model is Integral to Achieving Data-Driven Success

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Quality data is an absolute must for modern-day businesses to taste success. Similarly, poor quality, unverified data can lead to significant losses and missed opportunities. Ensuring all available data is of high quality is a critical capability for organizations aiming to rise up the data maturity ladder or seeking to join the data-driven club. Enabling organizations to achieve this goal is a sound data governance practice that modulates the availability, usability, integrity, and security of the data used within an organization. It pertains to the development of policies, procedures, and standards that govern data management through its lifecycle, from creation and collection to archiving and deletion. 

Primarily data governance helps establish a framework that enables organizations to effectively manage their data assets in compliance with prevailing regulatory requirements and organizational policies. The data governance framework defines the roles and responsibilities of data management besides outlining data quality standards and security measures. The framework also underlines processes for data access, sharing, and utilization.

Why data governance is essential to achieve data-driven success?

As emphasized earlier a sound and robust data governance model is essential for data-driven success as it ensures that data is accurate, consistent, and accessible to those who need it when they need it while ensuring that it is adequately protected. Here’s how data governance helps you achieve data-driven success.

  • Ensures data quality: a defined framework governing the recording of data ensures that the data is correctly entered into the system and that it is updated regularly making sure that the quality of available data is accurate and consistent across all business units.
  • Easy discovery of essential data: a robust data governance model ensures that data is organized and discoverable. This enables organizations to easily identify and access relevant data required to make timely business decisions.
  • Drives compliance: an essential premise of a sound data governance model is to adhere to regional data compliance standards and regulations such as GDPR, HIPAA, CCPA, and others.
  • Mitigates unwarranted risks: handling data can be quite tricky, especially with online fraudsters keeping a hawk’s eye for loopholes. A robust data governance model ensures that all data is secure and protected from unauthorized access, safeguarding the interests of your business at all times.
  • Confidence in available data: a thoughtfully designed data governance model bodes confidence amongst users as it provides the much-needed assurance on the quality and reliability of the data available. Confidence in available data brings agility to the process of decision-making.
  • Enables collaboration: data governance is essential to drive collaboration between teams within an organization and with external stakeholders basis a common language and standards for data management.

A sound governance practice is essential to ensure systems do not run rogue. As is the case with any institution and practice a sound data governance model clearly identifies and lists out the prerequisites and criteria for data collection, storage, and processing. A defined data governance model ensures that the entire data life cycle is governed as per set guidelines and policies powering the organization on a charted path towards data-driven success.

Data governance is a must-have capability integral to Data Quality Management. In fact, data governance can be termed as the first step towards designing  and implementing a sound data management strategy and practice. Read our illustrative eBook to learn how you can build data you can count on steering your business in the right direction helping discover and utilize a treasure trove of high quality valuable data.

  • Innover Team  |  March 23, 2023   |  

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