Data quality tools for SQL Server

Data quality tools measure how good and useful a data set is to serve its intended purpose. High quality data can lead to better decision-making and faster insights as well as reduce the costs of identifying and dealing with bad data in the system. It can also save time and allow companies to focus on more important tasks.

iWay Data Quality Suite

iWay Data Quality Server (DQS) is a complete tool for complex data quality management. iWay DQS not only evaluates, monitors, and manages the quality of data in different information systems, but it also prohibits inaccurate data from being admitted into those systems.

Commercial: Commercial
Data cleansing: Yes
Data Discovery & Search: No
Data Profiling: Yes
Data standarization: No
Free edition: No

Syniti Data Quality

Data quality management solutions from Syniti provide a simplified and cost-effective approach to monitor and accurately remediate data that violates your standards for data quality. Derive data quality rules from institutional knowledge, technical needs of downstream systems and interfaces, as well as legal/regulatory requirements. Proactively identify operational insights that allow potential issues to be addressed before process interruptions occur.

Commercial: Commercial
Data cleansing: Yes
Data Discovery & Search: No
Data Profiling: Yes
Data standarization: No
Free edition: No

CloverDX

CloverDX's data quality features offer you automated data quality and error handling for your workflows. With CloverDX's data quality features, you can discover and deal with bad data fast. You can automate bad data identification & correction, rule definitions, and reports on data quality. In short, CloverDX gives you the ability to make better decisions with more trustworthy data.

Commercial: Commercial
Data cleansing: Yes
Data Discovery & Search: Yes
Data Profiling: Yes
Data standarization: No
Free edition: No


Data quality tools are the scripts that support the data quality processes and they heavily rely on identification, understanding, and correction of data errors. Data quality tool enhances the accuracy of the data and helps to ensure good data governance all across the data-driven cycle.

The common functions that each data quality tools must perform are:

• Data profiling
• Data monitoring
• Parsing
• Standardization
• Data enrichment
• Data cleansing

Choosing the right data quality tool is essential and impacts the final results. To help you with the right selection, we prepared a list of tools that will assist you with maintaining a high level of data quality.