Data quality pertains to the accuracy, completeness, consistency, timeliness, and relevancy of data. Poor data quality can result in expensive mistakes, lost chances, and decreased efficiency. As per the most recent report by Gartner, businesses suffer an average loss of $15 million per year due to low data quality. Several tools for data quality have emerged in the market to tackle these challenges, each with distinct characteristics and abilities. These tools typically offer a range of functionalities, including data profiling, data cleansing, data matching, and data monitoring.
SnowDQ – Data Quality Tool combines all these features and functionalities in a single, easy-to-use platform, enabling organizations to improve data quality, reduce errors and redundancies, and drive better business outcomes. The tool integrates with Snowflake and Databricks and popular data catalog or metadata management systems, allowing for easy deployment and management on the cloud or on-premises. With its user-friendly interface and customizable rules, the tool can help businesses elevate their data quality and reduce the risks and costs associated with poor data quality.