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  3. DQLabs Platform
Logo of DQLabs Platform

DQLabs Platform

byDQLabs
in
4.6
Market Presence: Augmented Data Quality Solutions, Data Observability Tools

Overview

Product Information on DQLabs Platform

Updated 16th May 2023

What is DQLabs Platform?

DQLabs is an automated modern data quality platform that delivers reliable and accurate data for better business outcomes. DQLabs automates business quality checks and resolution using a semantic layer to deliver “fit-for-purpose” data for consumption across reporting and analytics. With an automation-first approach and self-learning capabilities, the DQLabs platform harnesses the combined power of Data Observability, Data Quality, and Data Discovery to enable data producers, consumers, and leaders to turn data into action faster, easier, and more collaboratively.

DQLabs Platform Pricing

For DQLabs, modern data quality platform pricing is based on a subscription model that is billed annually. The subscription fee is determined based on the number of data source connectors they want to use. With the standard license, customers will get three data source connectors and all the capabilities within Observe, Measure, Discover, and Product support.

DQLabs Platform Product Images

Discover Page
Discover Page
Measure Page
Measure Page

Overall experience with DQLabs Platform

Operations Associate
10B - 30B USD, Banking
FAVORABLE

“Enterprise Focus Enhances Data Governance but Platform Complexity Presents Challenges”

4.0
Apr 30, 2026
The platform provides a unified and enterprise ready approach by combining data quality, observability and metadata/context into a single solution, reducing tool fragmentation. From an enterprise standpoint, the platform feel well aligned for regulated and data driven organizations where trust, lineage and governance are critical
Engineering Engineer
50M - 250M USD, Hardware
CRITICAL

“Comprehensive Data Insights Offered Despite Lack of Null Profiling and Schema Alerts”

3.0
Apr 2, 2026
It offers a comprehensive view of the data health but misses basics like null profiling and schema drift alerts.

About Company

Company Description

Updated 24th October 2024

DQLabs is an augmented data quality and observability platform that assists organizations in delivering dependable and precise data to improve their business outcomes. The platform offers automation-first and self-learning features, combining Data Observability, Data Quality and Data Discovery. This enables data producers, consumers, and leaders to transform data into actionable insights quickly, easily, and in a collaborative manner.

Company Details

Updated 26th February 2025
Company type
Private
Year Founded
2020
Head office location
Pasadena, United States
Number of employees
51 - 200
Annual Revenue
<50M USD
Website
https://www.dqlabs.ai

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Key Insights

A Snapshot of What Matters - Based on Validated User Reviews

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Peer Discussions

DQLabs Platform Reviews and Ratings

4.6

(87 Ratings)

Rating Distribution

5 Star
64%
4 Star
33%
3 Star
2%
2 Star
0%
1 Star
0%
Why ratings and reviews count differ?

Customer Experience

Evaluation & Contracting

4.5

Integration & Deployment

4.5

Service & Support

4.5

Product Capabilities

4.6

Filter Reviews
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Reviewer's Job Function
  • Operations Associate
    10B+ USD
    Banking
    Review Source

    Enterprise Focus Enhances Data Governance but Platform Complexity Presents Challenges

    4.0
    Apr 30, 2026
    The platform provides a unified and enterprise ready approach by combining data quality, observability and metadata/context into a single solution, reducing tool fragmentation. From an enterprise standpoint, the platform feel well aligned for regulated and data driven organizations where trust, lineage and governance are critical
  • Director Of Product Management
    50M-1B USD
    IT Services
    Review Source

    DQLabs' Impactful Platform Transforms Data Quality Management

    4.0
    May 27, 2026
    DQLabs provides a modern and innovative Data Quality platform that caters to all core areas of Data Quality. The platform is easy to use and provides basic and advanced capabilities that helps customers implement the platform in a methodical manner that is geared to scale depending on the platform usage. Basic features including Data Profiling, a library to maintain & execute DQ rules and provide insights in the form of dashboards/widgets. More advanced capabilities includes observability and remediation (that uses AI behind the scenes), auto discovering sensitive data based on pattern matches and more.
  • Data And Analytics Manager
    <50M USD
    IT Services
    Review Source

    Reliable Platform for data quality management

    5.0
    May 13, 2026
    the platform has been overall good across multiple data sources it has helped us to reliabliy for data's quality management , profiling and monitoring , its automation capabilities reduce our manual efforts specially data validation and rule management.
  • Data and Analytics Manager
    <50M USD
    Banking
    Review Source

    Tool Excels in Monitoring but Faces Limitations in Reporting

    4.0
    May 12, 2026
    They have been great partners by adding and enhancing functionality based on our feedback. Our assigned Project Manager has been very knowledgeable and attentive to our needs, he feels like an extension of our team since he makes himself available and quickly responds to our requests in spite of our time zone difference. The features of the tool takes care of the identification of data quality issues and allows our team to focus on solving issues instead of trying to identify them.
  • Software Developer
    10B+ USD
    Software
    Review Source

    Data Quality Platform Offers Breadth of Features With Some Onboarding Challenges

    5.0
    May 13, 2026
    overall experience with dq labs has been positive. it provides strong data quality and observability capabilities. good coverage for profiling, anomaly detection, etc. platform provides good scalability for enterprise environments. that said there's still room for improvement when it comes to ui/ux experiences, onboariding and integration.
...
Showing Result 1-5 of 102

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User Sentiment About DQLabs Platform
Reviewer Insights for: DQLabs Platform
Deciding Factors: DQLabs Platform Vs. Market Average
Performance of DQLabs Platform Across Market Features

DQLabs Platform Likes & Dislikes

Like

Unified platform: The integration of data observability data quality and data discovery within single control plane simplifies architecture and operational overhead. Cloud ecosystem integration: Seamless integration with modern data platforms and cloud services. (ex. Snowflake, AWS, Databricks) support cloud native data strategies. AI and automation first approach: Intelligent anomaly detection, automated rule suggestions and augmented remediation reduce manual efforts and improve time to detection for data issues.

Like

They have a full-fledged data quality solution. It can get lineage out of many different systems. You can parameterize and template everything.

Like

DQLabs provides rich DQ capabilities expected of a data quality toolset. Built-in Observability is a game changer for DQLabs.

Dislike

Cost considerations: subscription based pricing tied to connectors and scale can be a consideration for smaller teams or early stage deployments Advance tuning requires expertise: To fully benefit from AI driven capabilities and semantic modeling, organizations may need dedicated data governance or platform expertise. Learning curve: Due to the breadth of features, the platform can feel complex initially, especially for teams new to enterprise data quality and observability platforms

Dislike

The GUI's are tedious and slow. Push down optimization creates a view on the fly that requires a table lock which creates a mess. The generated SQL subqueries are not formatted which makes the analysis slow.

Dislike

Product Documentation and Installation deployment process needs to be improved. Need more real time customer use cases supported to mature further.