While all companies sell products or services, increasingly, the real value of a company rests in its data. As the value increases, so does the need to properly organize and store it and, just as importantly, protect it with good policies and procedures. Data governance policies consist of principles, guidelines, standards, roles, duties, and processes that ensure data quality and security throughout its life cycle. Although many businesses recognize the importance of data governance, they face challenges in consistently implementing best practices to make the most of their data.
Figure 3 from the full report Data Governance Best Practices shows where organizations are at each level of adoption. The three green bars make up the practice rate: 13% use data governance policies informally, 47% do so formally but inconsistently, and 22% do so formally and consistently (the maturity level). About 14% are in the process of implementing data governance policies, while only 4% of the respondents report no activity for this best practice.
The data suggest that a significant portion of organizations, 82%, are actively using data governance policies in some form. This indicates a growing awareness of the importance of this best practice. However, only 22% have achieved the most mature stage of consistent enforcement. This highlights a need for many organizations to improve their data governance practices by standardizing policies and ensuring consistent application across the board. On the bright side, the presence of organizations in the implementation stage (14%) suggests ongoing efforts to increase the use of data governance practices within the industry.
Data governance policies improve business intelligence and analytics by ensuring the data’s accuracy, consistency, and reliability. Without these, data integrity and reliability suffer, leading to poor decision-making. Moreover, at a time when data security and privacy are primary concerns, data governance policies pave the way for detailed security policies and procedures, such as access controls, encryption, and network monitoring. The security and privacy aspects of data governance are only becoming more critical as enterprise applications of generative AI may be trained on large amounts of enterprise data, potentially exposing the data to security and privacy risks.
“While most organizations recognize the value of data governance, consistent enforcement remains a challenge,” said Asif Cassim, principal analyst for Avasant Research, based in Los Angeles. “This highlights the need to bridge the gap between policy creation and implementation for effective data security and informed decision-making.”
Although the benefits of data governance policies are clear, organizations may face challenges in establishing them. It is difficult to govern data consistently if an organization stores its data in silos. Organizations seeking to create a uniform, standardized view of the data will run into problems if different departments adhere to different standards regarding data definition and data formats. Effective data governance is further hindered by inadequate technology infrastructure, with few organizations willing to invest in new systems to make it easier.
In our full report, we describe why data governance is an important process and the challenges it faces. We also study data governance adoption and practice levels, examining those by organization size and sector. We conclude with best practice suggestions on what every data governance policy should include. This best practice is one of 35 that we analyze in our annual IT Management Best Practices study.
This Research Byte is based on our report Data Governance Best Practices. The full report is available at no charge for subscribers, or it may be purchased by non-subscribers directly from our website (click for pricing).