What is data quality monitoring and why is it important?

What is data quality monitoring and why is it important?

Data quality monitoring involves tracking and assessing the quality of data over time. It's crucial because high-quality data leads to better decision-making.

What are the key metrics used in data quality monitoring?

Key metrics include accuracy, completeness, consistency, timeliness, and uniqueness. These help evaluate the overall quality of data.

How can organizations implement data quality monitoring?

Organizations can implement it by establishing data governance frameworks, using automated tools, and regularly reviewing data quality metrics.

What tools are available for data quality monitoring?

There are several tools like Talend, Informatica, and Apache Griffin that help in monitoring and improving data quality.

Can you give examples of data quality issues?

Sure! Common issues include duplicate records, missing values, and incorrect data formats, which can all impact analysis.