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Microsoft Corporation

Microsoft Data Quality Services

Composite Score

8.5 /10

CX Score

8.9 /10

33 Reviews Write a Review

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What is Microsoft Data Quality Services?

SQL Server Data Quality Services (DQS) is a knowledge-driven data quality product. DQS enables you to build a knowledge base and use it to perform a variety of critical data quality tasks, including correction, enrichment, standardization, and de-duplication of your data. DQS enables you to perform data cleansing by using cloud-based reference data services provided by reference data providers. DQS also provides you with profiling that is integrated into its data-quality tasks, enabling you to analyze the integrity of your data.

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Microsoft Data Quality Services Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on Microsoft Data Quality Services.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

91 Likeliness to Recommend

1
Since last award

96 Plan to Renew

1
Since last award

87 Satisfaction of Cost Relative to Value

2
Since last award

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Emotional Footprint Overview

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+93 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love Microsoft Data Quality Services?

0% Negative

7% Neutral

93% Positive

Pros

Respectful
Performance Enhancing
Unique Features
Security Protects

Feature Ratings

Average 81

Data Monitoring and Administration

Data Cleansing

Data Source Connectivity

Record Deduplication

Record Management

Reporting Components

Data Matching

Data Profiling

Dashboard

Data Enrichment

Geocoding

Vendor Capability Ratings

Average 83

Business Value Created

Quality of Features

Ease of Customization

Product Strategy and Rate of Improvement

Ease of Data Integration

Ease of IT Administration

Ease of Implementation

Availability and Quality of Training

Vendor Support

Usability and Intuitiveness

Breadth of Features

Microsoft Data Quality Services Reviews

Sourabh P.

Role: Information Technology
Industry: Technology
Involvement: IT Leader or Manager

Validated Review

Verified Reviewer

Submitted Jul 2025

Solid for Basic Data Cleansing

Likeliness to Recommend

9 /10

What differentiates Microsoft Data Quality Services from other similar products?

Microsoft Data Quality Services (DQS) is unique in its tight integration with the Microsoft data ecosystem, especially SQL Server, SSIS, and Excel. This makes it easy for teams already using Microsoft tools to adopt without much overhead. Another differentiator is its knowledge-based approach, which allows users to build reusable rules and domain knowledge over time—helping improve data quality through learning.

What is your favorite aspect of this product?

My favorite aspect of Microsoft Data Quality Services is its seamless integration with SQL Server and other Microsoft tools like SSIS and Excel. This makes it easy to plug data quality processes directly into existing ETL workflows without needing separate platforms or complex setups. The knowledge base feature is also useful—it allows you to build and refine data rules over time, improving accuracy with each cycle. For teams already in the Microsoft ecosystem, this level of convenience and compatibility is a big win.

What do you dislike most about this product?

The biggest downside of Microsoft Data Quality Services is that it feels outdated and limited in scope. The user interface is not very intuitive, and the overall experience lacks the modern features you'd expect—like AI-driven suggestions, real-time validation, or robust cloud support. It also doesn’t scale well for large, complex datasets or hybrid environments. If you’re working with diverse data sources or need deep customization, DQS can feel restrictive and behind the curve.

What recommendations would you give to someone considering this product?

Best for Microsoft-Centric Environments: DQS works well if you're already heavily invested in SQL Server, SSIS, or Excel. It integrates smoothly and can be effective for basic data cleansing and validation tasks. Use for Simple to Moderate Use Cases: If your data quality needs are straightforward—like removing duplicates, standardizing values, or applying domain rules—DQS will likely meet your expectations. Be Aware of Limitations: It’s not ideal for real-time processing, cloud-native setups, or highly complex data pipelines. If your use case demands those, you might want to explore more advanced tools.

Pros

Helps Innovate
Continually Improving Product
Performance Enhancing
Enables Productivity

Ndianaobong B.

Role: Consultant
Industry: Technology
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Jun 2025

Solid Data Cleaning Tool

Likeliness to Recommend

10 /10

What differentiates Microsoft Data Quality Services from other similar products?

DQS builds a reusable knowledge base from your data and third-party reference sources, enabling automated correction, standardization, deduplication, and enrichment

What is your favorite aspect of this product?

Its knowledge-base-driven automation for cleansing, standardizing, and enriching data—without writing complex SQL—is a major productivity booster for data-focused teams.

What do you dislike most about this product?

The outdated, clunky GUI—which hinders usability and makes navigation and operation feel less intuitive for today’s data practitioners.

What recommendations would you give to someone considering this product?

Before implementing DQS, establish a robust data governance framework—complete with clear quality standards, regular profiling and cleansing workflows, continuous monitoring, and defined roles—for maximum impact and usability.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

Manish S.

Role: Information Technology
Industry: Technology
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Jun 2025

Best tool for Duplicate Removal and data cleaning

Likeliness to Recommend

8 /10

What differentiates Microsoft Data Quality Services from other similar products?

The best thing about MS DQS is that it has a policy wizard that helps with fuzzy logics with deduplication of data. It has built-in integration with SSIS, allowing users to streamline workflows which I believe makes it outstanding.

What is your favorite aspect of this product?

What I like most about using MS DQS is its smooth integration with SQL Server. I also like its performance for data and its usefulness in deleting duplicates in data easily.

What do you dislike most about this product?

I do not like the UI much as it feels very outdated, and it has less support for unstructured data, which requires workarounds.

What recommendations would you give to someone considering this product?

Well, this tool must have tool for data analyst although if your work is on unstructured data mostly then it may not be an appropriate fit.

Pros

Performance Enhancing
Unique Features
Efficient Service
Inspires Innovation

Microsoft Data Quality Services

What is Microsoft Data Quality Services?

Company Details

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Awards & Recognition

Microsoft Data Quality Services Ratings

91 Likeliness to Recommend

1 Since last award

96 Plan to Renew

1 Since last award

87 Satisfaction of Cost Relative to Value

2 Since last award

Emotional Footprint Overview

+93 Net Emotional Footprint

How much do users love Microsoft Data Quality Services?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Data Monitoring and Administration Includes ability to continuously monitored data quality rules, as well as generate alerts to notify data stewards when they need to address an issue.

Data Cleansing Includes data auditing, workflow specification, post-processing, and controlling. such as address standardization and the correction of known invalid values.

Data Source Connectivity Includes abiity to connect to a wide selection of data source types and systems.

Record Deduplication Identity resolution is the process of linking various records and is the main engine for record deduplication, which can enable some aspects of data cleansing.

Record Management Includes ability for Data stewards to monitoring data quality, taking action to determine the root cause of flagged issues and recommending remediation actions.

Reporting Components Lightweight controls and components that are easily embeddable and reusable. Integration with common apps such as Word, Excel, etc.

Data Matching Includes fuzzy matching, data comparison, and data merging.

Data Profiling Includes statistical analysis of data values to evaluate the frequency, distribution and completeness of data.

Dashboard Includes alerts and notifications, KPIs, visual analytics, and interactive features.

Data Enrichment Includes the enhancement of the value of internally held data by appending related attributes from external sources .

Geocoding Includes geo-referencing, address validation and verification, data mapping, and data append.

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Microsoft Data Quality Services Reviews

Sourabh P.

Solid for Basic Data Cleansing

Likeliness to Recommend

Pros

Ndianaobong B.

Solid Data Cleaning Tool

Likeliness to Recommend

Pros

Manish S.

Best tool for Duplicate Removal and data cleaning

Likeliness to Recommend

Pros

Most Popular Microsoft Data Quality Services Comparisons

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1
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Feature Ratings

Data Monitoring and Administration

Data Cleansing

Data Source Connectivity

Record Deduplication

Record Management

Reporting Components

Data Matching

Data Profiling

Dashboard

Data Enrichment

Geocoding

Vendor Capability Ratings

Business Value Created

Quality of Features

Ease of Customization

Product Strategy and Rate of Improvement

Ease of Data Integration

Ease of IT Administration

Ease of Implementation

Availability and Quality of Training

Vendor Support

Usability and Intuitiveness

Breadth of Features