{"id":15784,"date":"2023-04-21T07:45:52","date_gmt":"2023-04-21T07:45:52","guid":{"rendered":"https:\/\/education.telefony-taksi.ru\/?p=15784"},"modified":"2023-04-24T17:34:51","modified_gmt":"2023-04-24T17:34:51","slug":"5-best-data-quality-tools-for-your-use-in-2023","status":"publish","type":"post","link":"https:\/\/education.telefony-taksi.ru\/5-best-data-quality-tools-for-your-use-in-2023.html","title":{"rendered":"5 Best data quality tools for your use in 2023"},"content":{"rendered":"

\"Data<\/p>\n

Data quality tools are essential for businesses to make strategic decisions, achieve business objectives, and solve critical challenges. TechTarget defines data quality as a health condition of data based on factors such as accuracy, consistency, reliability, completeness, and whether it’s real-time or not. If the data is bad, it can cost organizations an average of $12.9 million every year, according to a Gartner report . On the other hand, 80% of companies see a surge in revenue after implementing good and real-time data.<\/p>\n

In this context, data quality tools play a pivotal role in determining the health of data. They examine the data to ensure it is good enough to make informed business decisions. Let’s discuss the top data quality tools, and their pros and cons, to help you make the right choice for your organization.<\/p>\n

What are Data Quality Methods?<\/h2>\n

IBM describes a data quality method as a process organized by analytical functions to provide in-depth knowledge and best practices for data quality strategies. There are different types of data quality methods, which include:<\/p>\n

Data Validation Through One or More Sources<\/h3>\n

The data validation process involves the implementation of predefined rules and knowledge to validate the integrity of data through single or multiple databases.<\/p>\n

Conducting Data Quality Studies<\/h3>\n

This systematic process is about designing and executing data quality assessment studies to determine the health condition of the data.<\/p>\n

Identification and Validation of Data condition<\/h3>\n

Identification of the data condition process is also known as case definition or case finding. In this process, data analysts use predetermined rules to identify and validate the data health condition.<\/p>\n

Best Data Quality Tools<\/h2>\n

\"Best<\/h2>\n

Data is the lifeblood of an organization and has a significant impact on business outcomes. That’s why it’s pivotal for companies to have the right set of data quality tools to determine the health of the data they are relying on. Here is a list of the top five data quality tools to consider for your data quality management process.<\/p>\n

1. Ataccama<\/h3>\n

Ataccama ONE is an open-source data management platform that consolidates data governance, data quality, and data management in a single, AI-enabled platform across hybrid and cloud environments. Integrating Ataccama ONE enables data teams to accelerate their business decisions while maintaining data trust, security, and governance.<\/p>\n

Include data discovery and profiling, metadata management, data catalog, and data quality management<\/p>\n