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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
This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions.
Engineering Engineer
50M - 250M USD, Hardware
CRITICAL

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

3.0
Apr 2, 2026
This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions. This text serves as a placeholder and does not reflect the user’s review responses or opinions.

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

(89 Ratings)

Rating Distribution

5 Star
62%
4 Star
36%
3 Star
2%
2 Star
0%
1 Star
0%
Why ratings and reviews count differ?
  • 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
  • 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
  • Read All 104 Reviews

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Recommended Gartner Insights

  • Critical Capabilities for Augmented Data Quality Solutions
  • Magic Quadrant for Augmented Data Quality Solutions
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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

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

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.

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

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

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.