What is data integrity?

Data integrity is the overall quality and reliability of data. Maintaining accurate, reliable, and consistent data helps to save on time, energy, and costs.

Data integrity differs from data security, which is the protection of data from various threats and privacy violations. Like data security, data integrity also faces threats, such as: 

• Human error

• Formatting errors

• Collection errors

These errors threaten to compromise data integrity to the detriment of the positive outcomes produced by data-driven decision-making, which fundamentally relies on data integrity.

Why Is Data Integrity Important?

Data integrity is critical to support data-driven decision-making, which improves customer satisfaction and retention, as well as profitability. Making effective data-driven decisions relies on maintaining accurate and complete data across multiple formats and over often long periods of time. 

How Is Data Integrity Maintained?

There are many ways to help uphold data integrity. You should start by assuring that both the concept and the importance of data integrity are understood by everyone involved in data collection, analysis, and communication. 

An organization-wide appreciation of data integrity helps to ensure all efforts are made with these principles in mind. An appreciation for the importance of data integrity is also necessary to design and implement procedures to verify the quality of relevant data and its interpretation. 

Another way to ensure data integrity is by protecting data from external threats, such as malware or more sophisticated means of stealing or damaging data.