Top 10 Tips to Improve Your Data Quality for Better Business Decision Making

In today's data-driven business landscape, organizations rely heavily on data analytics to make informed decisions. However, poor data quality can lead to significant financial losses and hinder effective decision making. According to Gartner, organizations experience an average annual cost of $12.9 million due to inadequate data quality. To address this challenge, data and analytics (D&A) leaders need to prioritize data quality improvement as a competitive advantage. In this article, we will explore the top ten tips to enhance data quality.

1) Establish the Impact of Improved Data Quality on Business Decisions:

Identify the connection between business processes, key performance indicators (KPIs), and data assets. By recognizing existing data quality issues and their impact on revenue and business KPIs, you can lay the foundation for a targeted data quality improvement program.

2) Define a "Good Enough" Standard of Data:

Engage in periodic discussions with business stakeholders to understand their expectations and define the organization's data quality standards. Different lines of business may have varying standards and requirements, so it is crucial to align everyone's expectations.

3) Establish a Data Quality Standard Across the Organization:

Develop comprehensive data quality standards that can be implemented consistently across all business units. This ensures that stakeholders understand and execute their operations in accordance with the defined data quality standard, fostering a culture of data excellence.

4) Use Data Profiling as a Continuous Process:

Data profiling helps identify data issues, enabling corrective actions and providing insights for improvement. Conduct data profiling regularly to uncover critical data quality issues and prioritize them based on their impact on business operations.

5) Design and Implement Data Quality Dashboards:

Create dashboards that provide stakeholders with a comprehensive overview of data quality, enabling them to monitor critical data assets and identify trends and patterns. These dashboards facilitate data-driven decision making based on reliable and trusted data.

6) Adopt a Trust-Based Semantic Model:

Recognize that data may originate from external sources with varying levels of governance. Instead of relying solely on a truth-based model, establish trust levels and implement mitigation measures when data trust is compromised.

7) Include Data Quality in Governance Board Meetings:

Link data quality initiatives to business outcomes and communicate the impact of data quality improvements in terms of business and revenue. Regularly provide the governance board with updates on data quality progress and challenges.

8) Define Data Quality Responsibilities within Data Steward Roles:

Appoint data stewards responsible for ensuring data quality and fitness for purpose. These stewards should champion good data management practices, monitor data quality, and escalate issues when necessary.

9) Establish a Special Interest Group for Data Quality:

Create a dedicated group comprising representatives from different business units, IT, and the chief data officer team to collaborate on data quality improvement. This collaborative effort ensures consistent best practices and mitigates risks across the organization.

10) Conduct Data Quality Reviews as Release Management Stages:

Implement regular reviews to track progress, make timely corrections, and ensure ongoing data quality. Share impactful best practices that have proven

Conclusion

In the pursuit of data quality excellence, Intelligent Delivery Solutions are a leading provider of Data Quality Specialists. With our expertise and experience, we can help your business unlock the full potential of your data. Whether you need assistance in establishing data quality standards, implementing effective data profiling techniques, or designing customized data quality dashboards, our team is ready to support you. Contact us directly to learn more about how Intelligent Delivery Solutions can drive data quality improvements and empower your business to make informed decisions with confidence.