Data quality rules ensure that data meets specific standards or criteria for accuracy, completeness, consistency, and reliability. These rules are established to maintain high-quality data that can be trusted for decision-making, analysis, and various other purposes within an organization.

By defining and enforcing data quality rules, organizations can improve the integrity and usefulness of their data assets, leading to better business outcomes and insights.

My role and responsibilities in this project were to:

• Write the data quality business rules from scratch with the support of the business

• Ensures that decisions are based on accurate and reliable information, leading to better outcomes and reduced risk in the business.

• Identifying critical elements in a process and ensuring their data quality can reduce errors, leading to increased efficiency and productivity.

• It reduces the need for rework and corrections, saving time and resources that would otherwise be spent fixing errors.

• Reliable data improves customer experiences by ensuring interactions are based on accurate information, increasing trust and satisfaction.

• Help ensure compliance with regulations and mitigate risks associated with incorrect or incomplete data, protecting the organization from legal and reputational issues.

• Quality data enables more accurate analysis and reporting, leading to deeper insights and informed decision-making.

• Identifying areas for process improvement and optimization, leading to increased effectiveness and competitiveness.