Last updated on Jul 7, 2024

Your company is rapidly expanding its data. How can you manage data governance with limited resources?

As your company grows, so does the volume of data you generate and collect. Managing this data effectively is crucial to maintaining the integrity, security, and usefulness of the information at your disposal. Data governance is the process of establishing policies, procedures, and standards for the effective management of data. However, limited resources can make this seem like a daunting task. Yet, with strategic planning and smart execution, you can implement a robust data governance framework that scales with your business.

1 Prioritize Data

Prioritizing which data requires governance is a practical first step when resources are scarce. You should focus on the most sensitive and business-critical data. This includes personal customer information, financial records, and proprietary business insights. By categorizing data based on its importance and sensitivity, you can allocate your limited resources to areas that will have the greatest impact on compliance, security, and business operations.

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Oluwabusayo Adigun, CDMP®

Top Data Governance Voice|Top Data Management Voice|Data Quality|Change Management
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A best practice in data governance implementation is identifying and focusing on critical data elements - CDEs at the preliminary stage. CDEs are identified collaboratively with business stakeholders based on data with the most impact on the business outcome. Since it is not feasible to focus on ALL data elements effectively, prioritizing CDEs is necessary. It helps focus on the most critical data and subsequently to less critical data in order of prioritization as data management maturity improves. Addressing the CDEs first enables data governance resources to be tailored towards the important business/enterprise data elements, thereby increasing the likelihood of recording early impact and success.

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2 Automate Processes

Leveraging automation can significantly reduce the workload involved in data governance. Simple tasks such as data classification, quality checks, and monitoring for compliance can often be automated with the right tools. Automation not only helps manage large volumes of data but also reduces the risk of human error. This ensures that even with a small team, your data governance efforts are consistent and efficient.

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3 Leverage Templates

Templates and frameworks for data governance policies and procedures can be incredibly beneficial. Instead of creating documents from scratch, you can adapt pre-existing templates to fit your company's needs. This approach saves time and ensures that your governance documents are comprehensive and in line with industry standards. Templates also help in maintaining consistency across different departments within your organization.

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4 Train Employees

Training your employees in data governance practices is a cost-effective way to extend your capabilities. By instilling a culture of data responsibility, every member of your team becomes a de facto data steward, aware of the importance of data quality and security. Regular training sessions can help employees understand their role in governance and ensure that they follow the established policies and procedures.

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Claudio A.

Engenheiro de Dados | Analista de Dados | IA | Machine Learning | BI l Especialista de dados
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Organize workshops e reuniões que definam metas comuns e criem uma visão compartilhada, reduzindo conflitos e garantindo que todos estejam focados nos mesmos resultados.

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5 Monitor Regularly

Regular monitoring of your data governance practices is essential to ensure they are effective and to make necessary adjustments. This involves auditing data usage, access controls, and adherence to policies. Monitoring can often be set up to run in the background, alerting you only when there are deviations from the norm. This proactive approach allows for early detection of potential issues before they escalate.

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6 Scale Smartly

As your company's data continues to grow, your data governance strategies should evolve accordingly. This means reassessing your priorities, automating additional processes, refining templates, and continuing employee education. Smart scaling involves being flexible and adaptive, ensuring that your data governance framework can accommodate new types of data, regulations, and business objectives without requiring a proportional increase in resources.

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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?

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Your company is rapidly expanding its data. How can you manage data governance with limited resources?

1

2

3

4

5

6

7

1 Prioritize Data

2 Automate Processes

3 Leverage Templates

4 Train Employees

5 Monitor Regularly

6 Scale Smartly

7 Here’s what else to consider

Data Governance

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Your company is rapidly expanding its data. How can you manage data governance with limited resources?

1

2

3

4

5

6

7

1 Prioritize Data

2 Automate Processes

3 Leverage Templates

4 Train Employees

5 Monitor Regularly

6 Scale Smartly

7 Here’s what else to consider

Data Governance

Rate this article

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