What is data quality management and why is it important?

What is data quality management and why is it important?

Data quality management involves processes to ensure the accuracy, consistency, and reliability of data. It's crucial for informed decision-making.

What are the key components of a data quality management strategy?

Key components include data profiling, data cleansing, data monitoring, and establishing data governance policies.

How can I implement data quality management in my organization?

Start by assessing your current data quality, define clear standards, and involve stakeholders in creating a data governance framework.

What tools are available for data quality management?

There are several tools like Talend, Informatica, and Microsoft Azure Data Quality Services that can help manage data quality effectively.

Can you give me examples of data quality issues?

Common issues include duplicate records, missing values, inconsistent formats, and outdated information.