5 Best Data Quality Tools for Your Use in 2023

5 Best Data Quality Tools for Your Use in 2023 | Data Science and Analytics | Emeritus

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. 

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.

Data Quality Tools

What are Data Quality Methods?

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:

Data Validation Through One or More Sources

The data validation process involves the implementation of predefined rules and knowledge to validate the integrity of data through single or multiple databases.

Conducting Data Quality Studies

This systematic process is about designing and executing data quality assessment studies to determine the health condition of the data.

Identification and Validation of Data condition

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.

Best Data Quality Tools

Best Data Quality Tools

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.

1. Ataccama

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.

Features 

Include data discovery and profiling, metadata management, data catalog, and data quality management

Pros

  • Exceptional data profiling abilities
  • Easy to use and flexible
  • Provide a fast data processing option

Cons

  • Time-consuming configuration process
  • Difficult to identify the cause of errors
  • Tough to get technical support because of its open-source feature

2. Informatica

Informatica provides multiple data quality services including data quality, master data management, big data quality, Axon data governance, and data as a Service. These help users develop a holistic view of data collected from disparate, duplicate, and conflicting sources.

Features

Include data integration, address validation, data quality, data profiling, and data security functionality

Pros

  • Offers a one-stop-solution with various services
  • Automates a wide range of data quality tasks

Cons

  • Lack of open-source version leads to a high maintenance fee, which is expensive
  • Incompatible with other technologies because it doesn’t support the integration of code written in languages like Java, Python, and R

3. Innovative Systems

Innovative Systems provides Master Data Management (MDM) solutions for operational and analytical functions. Its Enlighten platform is an integrated data quality software that gives unified and customizable solutions to customers.

Features

Include data profiling, data discovery and monitoring, and a holistic view of data that helps users extract meaningful insights

Pros

  • Easy to operate and customized
  • Preferable for data matching process
  • Offers product support

Cons

  • Interface for developing workflows is unclear
  • Compatible with Windows only

4. Oracle

Oracle’s Cloud Infrastructure Data Catalog is a metadata management service that enables companies to discover and control data using an organized stock of data assets.

Features 

Include an advanced, intuitive user interface (UI) that encompasses a simple, user-friendly dashboard, search and browse abilities, suggested actions, and shortcuts

Pros

  • Cloud-based, hence accessible anywhere using any device 
  • Offers a one-stop-solution

Cons

  • Restricted data export 
  • Complicated to navigate

5. Precisely

Precisely is a data quality tool that helps users achieve data integrity with accuracy and consistency. It offers multiple data quality solutions such as Trillium for big data, Trillium data quality, and Trillium cloud, which help users make informed and quick business decisions with an in-depth understanding of data.

Features 

Includes data cleansing, data profiling, and data standardization 

Pros

  • Provides strong customer support
  • Offers multiple solutions under one umbrella

Cons

  • Complex to use
  • Complex installation process and User Interface (UI)

How to Choose the Right Data Quality Tool

Given the multiple data quality tools available in the market, deciding on the right one can be difficult. But the choice is important as the right data quality tool can help businesses make informed decisions. Here are some important tips to help you with the selection. 

  • Identify the data-related challenges your business is facing
  • Understand the type of data quality tools to help you solve those challenges
  • Be aware of the pros and cons of data quality tools to support your decision
  • Investigate the pricing plan and select the tool as per your allocated budget

Becoming Data-Savvy with Emeritus

Data empowers business decisions but if data is bad or irrelevant, it can lead you in the wrong direction. Hence, improving data quality using the above-mentioned tools is essential. To understand more about data-related tools and strategies, explore the various online courses on the Emeritus platform, offered in collaboration with leading global experts.

Write to us at content@emeritus.org

Data Quality Tools

About the Author

Content Writer, Emeritus Blog
Sanmit is unraveling the mysteries of Literature and Gender Studies by day and creating digital content for startups by night. With accolades and publications that span continents, he's the reliable literary guide you want on your team. When he's not weaving words, you'll find him lost in the realms of music, cinema, and the boundless world of books.
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