What are the 5 C's of data quality?

The 5 C's of Data Quality

Working as a Data Quality Control Specialist means making sure information is actually useful for the people relying on it. To keep data reliable, professionals look at 5 core dimensions often called the 5 C's of data quality.

Completeness ensures that no vital information is missing from your datasets. If fields are left blank, analyses can easily become skewed.

Consistency means that data matches across multiple systems and databases without contradictory entries or conflicting values.

Accuracy checks whether the recorded data actually reflects the real-world values it represents. Inaccurate data leads straight to flawed business decisions.

Timeliness focuses on whether information is available when it is needed. Data that arrives too late loses its value, no matter how accurate it is.

Validity guarantees that the data conforms to the defined business rules, formats, and structural constraints required for analysis.

By monitoring these factors using data validation software and specific quality metrics, organizations can maintain high integrity and trust in their daily operations.