What is Data Quality?

Data Quality involves standardization and enrichment of data and is essential to the reliability of the data analytics that drives effective business intelligence decisions. Data quality encompasses the accuracy, completeness, consistency across data sources and relevance of data. Data quality is affected by the way data is entered, stored and managed. Specific requirements must be defined for cleaning and standardizing the data.

Data Quality involves standardization and enrichment of data and is essential to the reliability of the data analytics that drives effective business intelligence decisions. Data quality encompasses the accuracy, completeness, consistency across data sources and relevance of data. Data quality is affected by the way data is entered, stored and managed. Specific requirements must be defined for cleaning and standardizing the data. Rules are established for certifying the quality of the data and these rules are integrated into an existing workflow to both test and allow for exception handling.

Poor Data Quality is one of the biggest barriers to effective business intelligence deployments. Data Quality services need to provide a complete solution to identify, define and cleanse data while monitoring data quality over time regardless of the amount or size of the data. Data de-duplication, standardization and validation is necessary to enable clean and high-quality data for access, reporting and analytics. Because rules, needs and data sources change and are added continuously and data quality services need to be scalable and able to address new requirements in order to be successful.