Data Governance and Data Analyst Collaboration

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Data Governance and Data Analyst Collaboration

Data Governance and Data Analyst teams were born to collaborate. The Data Governance team typically plays a supporting role in ensuring that data is both accurate and trustworthy. Both teams align with the organization's business strategy to deliver insights, adhere to compliance needs, and provide relevant information for critical business decision-making.

A Data analyst is responsible for analyzing large amounts of data and providing insights and recommendations to make crucial business decisions. They are in charge of presenting the data in an easily readable format to users in an organization. These results typically get showcased through a business report or visualization using maps, graphs, and charts. C-Suite, executive leadership, middle managers, shared services, and general users of the data all benefit from these insights and reports to conduct business and make future decisions. 

 

The Data Governance team ensures that the “data quality score” meets the standards set by the business so data analysts use trusted and accurate data when creating reports or insights for business users. The need for governance and easily accessible data is essential for data analysts to conduct their job function properly. Data Lineage also plays a crucial role as Data Analysts will often need to know, “where this data came from?” The data governance team will document and confirm data lineage through manual and automated processes.

In a recent DataQG Community survey, more than 33% of data governance professionals rated data quality as the most important element within their data governance program. This was followed by data stewardship, data lineage, and master data.

Vocabulary, definitions, and standardized business language will often be defined and managed by both data analysts and data governance teams. Data analysts will use this common terminology when showcasing results from data to relevant stakeholders. A “business glossary” is a foundational collaboration tool for both teams to ensure standardization for users and business partners. 

The data governance team also creates a process to protect data for unauthorized users within an organization. Data privacy standards and rules get implemented to ensure PII and other sensitive information is not accessed or shared by teams or individuals who do not have access. Data analysts will consume the data once it is prepared for discovery and consumption. 

These are just some collaboration methods and practices that data governance and analyst teams encompass daily. Data lineage, quality, security, privacy, accuracy, and consistency will bring confidence when reports and visualizations are created for business strategy and delivery. The relationship between both functions is crucial in a successful data vision and strategy.