Mainnet Musings and Keeping Data Secure

With October being Cybersecurity Awareness Month, can you speak to why companies should prioritize data governance and the importance of keeping data secure?

The discipline of Enterprise Data Governance should work “hand in glove” with any organization’s cybersecurity capabilities for a number of key reasons, such as:

• Data governance helps to define where sensitive corporate data exists across the enterprise data estate. In the event of a cyber incident, knowing where points of infiltration may have accessed privacy-regulated data in the shortest amount of time is of critical importance.
• Data governance defines and maintains policies for the protection and appropriate use of enterprise data. These policies may help cyber teams identify the criticality and severity of cyber events.
• Data governance establishes data ownership within the organization, which identifies corporate contacts that may be called upon in the event of a cybersecurity event.

Given that data ecosystems are currently highly fragmented, what are some of the best practices companies should consider implementing when it comes to data governance?

It’s critical for companies to establish what key data assets (often referred to as data “domains”) require well-defined protection protocols based on sensitivity levels, ownership and policies. Importantly, companies should focus on the most critical data to start to avoid trying to do too much and risking not driving value.

Additionally, companies should have corporate-wide data literacy and education efforts, establishing the importance of data governance and driving buy-in and compliance across all organizational levels.  

How do you think data governance will evolve in the next decade?

Forward leaps in AI will transform many of the labor-intensive activities that require significant human capital and data governance software. Examples include data classification, duplication-management in master and reference data, data lineage and traceability, to name a few areas. Data governance organizations will also begin taking on more responsibility around AI/GenAI governance, including establishment of ethical use, guardrails, and more.