5 Best data quality tools (and how to find the right one)

With modern data environments growing in scale and complexity and AI taking center stage, data quality management is no longer optional. Organizations must ensure that they are actively managing the quality of their data. 

The data quality tool you choose can make or break your data strategy. Choosing the best data quality tools can mean the difference between good data and bad data for your organization. With great data quality tools, you can streamline workflows, save time, ensure compliance, and deliver trusted data for smarter decision-making. With the wrong tool, however, you can add complexity, slow down your teams, and leave your data less reliable than before.

In this blog, we’ll look at five leading data quality tools, outlining their strengths and ideal use cases so you can choose the right one for your organization.

What is data quality?

Data quality measures the usability of your data and highlights why organizations need data quality management tools and data quality management software. Data quality can be measured against six key dimensions: completeness, validity, timeliness, uniqueness, accuracy, and consistency.

Learn more about data quality and its importance.

5 best data quality tools on the market

To help you make a decision on the right data quality tool for you, we’ve listed the key features, strengths, ideal use cases, and trade-offs of the top five data quality solution tools below.

1. Ataccama data quality software

Ataccama has been a leader in data quality management since 2007, providing businesses with the trusted, high-quality data they need to thrive. Ataccama ONE combines intelligent automation with a unified approach to managing, monitoring, and improving enterprise data.

With Ataccama ONE, you can seamlessly:

• Establish a comprehensive data catalog. Gain a clear understanding of your data landscape by documenting and organizing your data assets.
• Ensure data accuracy and consistency. Utilize powerful data quality rules and automated workflows to identify and rectify data inconsistencies, ensuring your data is reliable and trustworthy.
• Proactively prevent data issues. Implement robust data quality checks and validation rules to catch errors before they impact your business.
• Understand data movement with data lineage. View traceability for audits and reporting, and get full visibility into dependencies and transformations for root cause analysis.
• Govern your data effectively. Define and enforce data policies and procedures to maintain data integrity and compliance.

All of this is powered by advanced AI, enabling intelligent automation and effortless data management. Ataccama ONE provides a user-friendly interface and a comprehensive suite of capabilities that surpass the competition, giving you the tools you need to unlock the true potential of your data.

Key features:

• AI-powered data quality
• Data profiling & classification
• Centralized, reusable rule library
• Data quality monitoring
• Anomaly detection
• Data observability
• Data lineage
• Data cleansing & standardization
• Automated data enrichment
• Record-level issue remediation
• Real-time data quality validation in pipelines

Strengths: Ataccama ONE stands out as an AI-powered, end-to-end data quality solution that helps organizations manage data quality at scale across their hybrid and multi-cloud environments.

2. Informatica

Informatica provides data quality and observability software, focusing on proactive measures to ensure high-quality data. Their tool builds trust in an organization and has advanced automated capabilities thanks to AI. They also deliver an enriched customer experience by providing instant and accurate access to frequently updated information.

Key features:

• Automated and scalable data profiling
• Prebuilt AI-powered rules
• Boosted data observability

3. Talend

Talend offers data quality solutions that profile, clean, and standardize data across your systems. They also emphasize the trust and interconnectedness of data teams and provide machine learning-powered recommendations for addressing data quality issues.

Key features:

• Built-in “trust score” for evaluating data
• Automatic data enrichment
• Compliance as a priority

4. IBM InfoSphere QualityStage

IBM’s InfoSphere offers capabilities for generating and monitoring data quality. It’s explicitly designedto support data quality and governance initiatives by providing a consistent and accurate view of your organization’s key data entities (e.g., customers, vendors, locations, products).

Key features:

• Data lake governance
• Unified platform
• Compatible with other IBM software

5. Precisely Trillium Quality

Precisely’s Trillium quality delivers enterprise data quality built for business. It is a data quality tool that scales and supports changing business needs as your organization grows. It’s deployable in batch or real-time, on-premises, or in the cloud.

Key features:

• Versatile deployment
• 360 customer view
• Global verification rules

Why are data quality tools important?

As mentioned earlier, data quality toolsenable your business to use your data more strategically. Here are some other reasons they’re important:

• Better decision-making. When reliable data is delivered to your executives in a timely manner, they can use it to make better-informed decisions that benefit your business.
• Increased speed of data teams. Data users spend most of their time cleansing and preparing data so that it’s accurate and fit for use. By managing data quality and ensuring high-quality, trusted data is available, you cut out this step and enable data users to start on projects right away.
• Avoid bad data quality. Bad data quality can hinder decision-making, leading to incorrect conclusions and bad business decisions.

How to choose the best data quality tool

If you’re still deciding which tool best suits your organization, let’s review some criteria to help you make your decision.

1. Assess your organization’s data quality needs

The volume and types of data your organization works with will heavily influence your tooling. Do you have large volumes of data? Is it growing? Do you need to focus on scalability? How much private data does your organization work with? Finding answers to these questions and internal auditing your data systems will help you pick the best tool.

2. Consider scalability and integration

As organizations grow, so do their data volumes. Whichever tool you choose needs to accommodate this growth and provide the flexibility necessary to process your data assets.

You also need to consider integration: Is the tool compatible with your current systems? Building a solution from the ground up or adapting existing systems to an incompatible tool will always be more costly and time-consuming.

3. Run a cost vs benefit analysis

Figure out the cost of the tool you want versus the time and savings it will provide. Consider the ROI of your data quality solution, as this will show the value you receive from implementing it.

4. Ask for customer reviews and case studies

Customer references and case studies are a great way to learn more about a data quality vendor. Search for customer stories that sound similar to your industry and use case. Any tool you choose should have a history of success with customers like your organization.

What features does a data quality tool need?

Regardless of the solution you choose, there are some features that all of the best data quality tools have. Here they are:

1. Ease of use and integration

You need a data quality tool that integrates with your existing data sources and systems. In addition, ease of use is an important characteristic. You want a tool that is intuitive and user-friendly, so that your team can learn how to use it quickly.

2. Accessible and scalable

Scalability is an important factor to consider when selecting a tool. As systems grow, entry portals multiply, and user roles diversify, so your data quality tool will need to be capable of handling larger volumes of data and numbers of source systems, as well as provide the ability to adjust access protocols accordingly.

3. Identifies inaccuracies and duplicates quickly

Any tool must be able to identify data quality issues rapidly and alert the relevant stakeholders right away. It should make it easy for end users to discover and address all data quality issues.

4. Supports data cleansing

Data cleansing is one of the most important roles of data quality management: cleaning up dirty data so it’s fit for purpose. The best data quality tools support automated cleansing, making the lives of data stewards easier so they don’t have to correct each record manually.

5. Enables ongoing monitoring

Data systems aren’t perfect. Even if you have comprehensive data quality rules, unexpected outliers and hiccups can slip through the cracks. Ongoing data quality monitoring tools continuously scan your data for issues, so no unwanted surprises reach your downstream systems.

6. Promotes data security

An organization’s data is only as secure as the tools it uses to manage and work with data. You need a tool with access permissions and significant barriers against hackers to prevent data leakage and other security-related mishaps.

7. Automated and customizable

Today, all data quality management tools have some form of automation. Automated processes like anomaly detection and data observability expedite the data quality process by recognizing issues and flagging them without human intervention.

No two organizations are the same, so solutions must be customizable in order to effectively address your organization’s unique needs.

Invest in the right data quality tool and unlock trusted data

Data quality tools are crucial for improving decision-making, increasing operational efficiency, and enhancing customer satisfaction by ensuring data is accurate, complete, and reliable. Learning about the leading tools on the market, their key features and strengths, and what to look for in a data quality tool can help you make the best choice for your organization’s needs.

Ataccama ONE empowers enterprises to automate, monitor, and improve data across the entire lifecycle.

Don’t hesitate to try Ataccama ONE, the trusted data quality management software for enterprises. We’ve been improving companies’ data assets for nearly two decades!