What strategies can you use to mitigate data governance risks as a data steward?

1 Assess the data landscape

The first step to mitigate data governance risks is to assess the current state of your data landscape. This means identifying the sources, types, owners, flows, and dependencies of your data assets, as well as the existing policies, standards, and processes that govern them. By conducting a data inventory, audit, or assessment, you can uncover the strengths and weaknesses of your data environment, as well as the gaps and opportunities for improvement. You can also prioritize the most critical data issues and risks that need your attention and action.

2 Implement data quality controls

The second step to mitigate data governance risks is to implement data quality controls throughout the data lifecycle. This means ensuring that your data is accurate, complete, consistent, timely, and relevant for its intended purposes. You can use various tools and techniques to monitor, measure, validate, and improve data quality, such as data profiling, cleansing, enrichment, standardization, and validation. You can also establish data quality metrics, indicators, and thresholds to track and report on data quality performance and issues.

3 Enforce data security and compliance

The third step to mitigate data governance risks is to enforce data security and compliance across your organization. This means protecting your data from unauthorized access, use, disclosure, modification, or loss, as well as complying with the relevant laws, regulations, and ethical standards that apply to your data. You can use various methods and technologies to safeguard your data, such as encryption, authentication, authorization, backup, recovery, and audit. You can also implement data policies, rules, and procedures to ensure that your data is handled in a lawful and responsible manner.

4 Promote data literacy and culture

The fourth step to mitigate data governance risks is to promote data literacy and culture among your stakeholders. This means educating and empowering your data users, producers, and consumers to understand, value, and leverage your data assets effectively and appropriately. You can use various channels and formats to communicate and collaborate with your data stakeholders, such as training, workshops, newsletters, dashboards, and feedback. You can also foster a data-driven culture that encourages data sharing, innovation, and accountability.

5 Align data with business goals

The fifth step to mitigate data governance risks is to align your data with your business goals and strategies. This means ensuring that your data supports and enables your organization's mission, vision, and objectives, as well as the needs and expectations of your customers and partners. You can use various frameworks and models to align your data with your business, such as the Data Value Chain, the Data Governance Maturity Model, or the Data Strategy Canvas. You can also define and demonstrate the value and impact of your data on your business outcomes and performance.

6 Review and update data governance practices

The sixth and final step to mitigate data governance risks is to review and update your data governance practices regularly. This means evaluating and adjusting your data governance processes, roles, and responsibilities to reflect the changing needs, challenges, and opportunities of your data environment. You can use various methods and tools to review and update your data governance practices, such as surveys, interviews, audits, benchmarks, and best practices. You can also seek feedback and input from your data stakeholders and experts to improve your data governance effectiveness and efficiency.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?