Data Quality Management: A Primer

Ensuring that data is of a standard quality across the organization is immeasurably important. The worth of a work place can easily be judged by the quality of its data. Sloppy organizations tend to have sloppy databases. Bad data can clutter your system, slow down work process and decrease efficiency. This is where data quality tools come into the picture.

As a basic definition, data quality tools are any processes, software or hardware that help you maintain a certain level of accuracy in data. It includes how reliable the data is. High quality data has about four qualities, and these are completeness, accuracy, availability and timeliness.

Data governance is another important aspect of data quality management. It essentially refers to a standardization process that all data entry and retrieval must subscribe to. Data governance helps reduce clutter, increase efficiency and speed up processes. While it can be a messy task to implement, the benefits of it far outweigh the negatives.

However, data governance has been proven to show results. Many business drivers now require organizations to institutionalize data governance. All industries can benefit from data governance. For instance, in a particular case study, a global asset manager across 25 countries set about data governance. After a detailed study of the needs and wants of the company, certain standards were set in place. The data queries were directed to third party data managers, which left the company to manage its core business.

Data stewards are highly important in an organization. They are responsible for management of data elements, both content and metadata. He/she has to ensure that every set of data entered into the system has clear element definitions, does not conflict with other entries in any way, has clearly numbered values, remove unused elements, has adequate documentation, sources and meets standards, ensures the metadata has all the necessary information, and protect the database from any unauthorized change or security attack. A good steward ensures that the data is consistently used, and prunes out unused data from the system, fosters ease of access of data across different divisions, and lowers costs with respect to migration.

Verdantis Integrity One is powered by process based AI based components which ensure data quality. It automatically classifies new item requests, structures information and streamlines data flow. It makes the ideal software partner for both data quality and data governance.


Jessica is one of the most passionate marketing professionals in Verdantis. She is a strong proponent of Data Quality Management for large enterprises. For her, data drives performance.