Data Quality Management Tools

Data quality management tools are software systems used to ensure users are always working with the highest quality, most up-to-date data available. Organizations rely heavily on these systems for functions such as:

  • Data cleansing—detecting and removing data containing typos, formatting errors, or other issues
  • Data deduplication—removing duplicate copies of data
  • Bulk updates and automation—updating or deleting multiple records at once, transforming data, finding and replacing, and automating repetitive, time-consuming tasks
  • Data validation—ensuring that data is accurate and up-to-date
  • Importing and exporting data—updating record data by importing from a spreadsheet and finding certain data to export to a spreadsheet
  • Integration—connecting to other software systems to combine disparate data sources

Who uses data quality management tools?

In the time of Big Data, more and more organizations are adopting data quality management tools to keep their data error-free and up-to-date. Since many organizations now work with vast amounts of data, many database management systems cannot process the kind of sweeping actions and complex processes that database administrators (DBAs) and data analysts need to perform. Using a data quality management tool shifts processing to a different system to improve functionality.

Plus, there are real consequences of using outdated, incorrect, or even partially correct data. Some of the most valuable companies in the world (Alphabet, Facebook, Tencent) deal heavily—if not almost exclusively—with data. High quality data is crucial for these companies to generate revenue.

But organizations of all sizes use data quality management tools. For example, many organizations use customer relationship management (CRM) software to store client contact information, job titles, interaction and purchase history, and data on how they interact with an organization’s website or emails. Storing incorrect or incomplete data on a client can lead to an awkward phone call at best and significant lost revenue at worst. Every organization works with data to some degree, and it’s important to make sure it’s reliable.

Webopedia Staff
Webopedia Staff
Since 1995, more than 100 tech experts and researchers have kept Webopedia’s definitions, articles, and study guides up to date. For more information on current editorial staff, please visit our About page.

Related Articles

@ Sign

Pronounced at sign or simply as at, this symbol is used in e-mail addressing to separate the user' name from the user's domain name,...

Munging

(MUHN-jing) Munging (address munging), is the act of altering an email address posted on a Web page to make it unreadable to bots and...

How to Create an RSS Feed

In the second installment of RSS how-to, we look at some of the nonrequired (optional) channel and item tags, discuss RSS specifications in-depth and...

Dictionary Attack

(n.) (1) A method used to break security systems, specifically password-based security systems, in which the attacker systematically tests all possible passwords beginning with...

ScalaHosting

ScalaHosting is a leading managed hosting provider that offers secure, scalable, and affordable...

HRIS

Human resources information system (HRIS) solutions help businesses manage multiple facets of their...

Best Managed Service Providers...

In today's business world, managed services are more critical than ever. They can...