In late October, a server misconfiguration at Microsoft left an endpoint publicly accessible with no authentication required. The lapse reportedly exposed 2.4 terabytes of data, including invoices, product orders, signed customer documents, partner ecosystem details, and other business transaction data.
While most people’s reaction to this news is likely, “Wait, what? Microsoft should know better,” this security event is the perfect example of why every organization—from giants such as Microsoft to two-person startups—needs to follow some data governance best practices and enforce strict data governance policies.
Data governance encompasses all of the internal policies, standards, and processes organizations use to define who can access data, how it can be collected, where it can be stored, and how it should be disposed of.
A solid data governance strategy not only protects sensitive enterprise data from loss and misuse but also improves business analytics and intelligence by ensuring data is accurate and consistent across the organization.
Data governance requires support from multiple roles to set and enforce policies and maintain compliance with both internal and governmental mandates.
Here are a few key team members every data governance program needs:
Chief data officer: Leads the organization’s data governance efforts
Data governance committee: Responsible for setting data governance policies and defining data use processes
Data owners: Directly responsible for keeping data secure and maintaining data quality
Data stewards: Champions the data governance program by training employees and enforcing policies
The right tools and technologies can simplify and streamline your data governance efforts. There are many different solutions out there, but at a minimum, consider adding these to your data governance toolbox:
Threat detection: Creates a line of defense against cyberthreats
Policy management: Assigns and enforces business rules for data usage
Data lineage: Tracks data from its origin through all applications and systems
Master data management: Provides a single source of truth for master data
Cataloging: Organize data into standardized catalogs
Every organization’s data governance needs are unique; however, there are several core data governance best practices that every organization should include in its strategy.
Classifying data into categories based on metadata, such as file type and contents, provides critical information needed to standardize data across all systems and applications.
Because data is sourced and shared across numerous applications and systems, enforcing a standardized format ensures the data is always accessible and accurate.
A strong business case that demonstrates the value and improvements a comprehensive data governance program provides is essential for getting and maintaining support from leadership.
Putting the right people in the right roles helps ensure policies and procedures are implemented and enforced organization-wide.
Track metrics over time to generate data-backed evidence that your data governance program is improving data quality, security, and compliance for the organization.
Automating governance processes saves time and resources and reduces risk by automatically enforcing governance policies and eliminating opportunities for human error.
Data governance impacts everyone in the organization, so it’s important to make progress visible, acknowledge challenges, and communicate openly with all stakeholders.
Review and revise your data governance plan regularly to keep up with employment and role changes, regulation updates, and new technology releases.
Organizations that are trying to increase their data governance maturity often find the most significant roadblocks are related to raising awareness of why the organization needs data governance in the first place.
Many organizations are stuck in the “But, we’ve always done it this way” mindset, which can make it difficult to enforce policies, get buy-in, and allocate the necessary resources for an effective data governance program.
The most powerful way to change this way of thinking is to clearly and specifically demonstrate the impact bad data has on your organization, whether through lost opportunities, compliance breaches, or inefficiencies that cost the company time and money.
Providing visibility into the role data plays in successful business outcomes makes it easier to show the value of a comprehensive data governance program and gain support from leadership.
At the risk of sounding cliche, it’s important to remember that data governance is a marathon, not a sprint. It’s an ongoing work in progress that will evolve over time in response to your data volume, risk profile, regulation changes, and countless other factors that impact how your organization’s data is managed, used, and protected.
Implementing these data governance best practices as a foundation for a comprehensive data governance strategy will help ensure your data is consistent, accurate, and secure across the organization.
If you’re ready to take a deeper dive into data governance, download your complimentary copy of our latest e-book: Navigating the Enterprise Data Governance Landscape.