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Informatica Rev VS Microsoft Data Quality Services

Compare Informatica Rev VS Microsoft Data Quality Services and see what are their differences

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Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI featured
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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Informatica Rev logo Informatica Rev

Informatica REV is a revolutionary new business user-focused full feautured data-prep tool that focuses on end-user simplicity.

Microsoft Data Quality Services logo Microsoft Data Quality Services

Data Quality
  • Informatica Rev Landing page
    Landing page //
    2023-03-17
  • Microsoft Data Quality Services Landing page
    Landing page //
    2023-10-02

Informatica Rev features and specs

No features have been listed yet.

Microsoft Data Quality Services features and specs

  • Integration with Microsoft Ecosystem
    Data Quality Services (DQS) seamlessly integrates with other Microsoft products, such as SQL Server and Azure, making it easier for organizations using Microsoft technologies to manage data quality within their existing infrastructure.
  • Data Cleansing and Matching
    DQS provides tools for data cleansing and matching, helping ensure data accuracy and consistency by identifying duplicates and standardizing data formats.
  • Knowledge Base Driven
    DQS utilizes a knowledge base approach to data quality, allowing users to define domain-specific rules and reference data for identifying and correcting data issues.
  • User-friendly Interface
    It offers a user-friendly interface that allows non-technical users to manage data quality processes without extensive database or coding knowledge.

Possible disadvantages of Microsoft Data Quality Services

  • Limited Advanced Features
    Compared to standalone data quality management tools, DQS may lack some advanced features and flexibility needed by large or highly complex organizations.
  • Performance Constraints
    As a component of SQL Server, DQS can encounter performance issues when handling very large datasets, potentially impacting the speed and efficiency of data processing.
  • Dependency on Microsoft SQL Server
    Organizations using non-Microsoft databases might face integration challenges, as DQS is heavily tied to the Microsoft SQL Server ecosystem.
  • Steep Learning Curve for Complex Configurations
    While basic features are relatively easy to use, managing more complex data quality processes can be challenging and may require technical expertise.

Informatica Rev videos

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Informatica REV Scheduler

Microsoft Data Quality Services videos

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Live Action: Microsoft Data Quality Services

Category Popularity

0-100% (relative to Informatica Rev and Microsoft Data Quality Services)

Informatica Rev

Microsoft Data Quality Services

Business Intelligence
100 100%
Business Intelligence
0% 0
Sales Tools
0 0%
Sales Tools
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Data Hygiene
0 0%
Data Hygiene
100% 100

User comments

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What are some alternatives?

When comparing Informatica Rev and Microsoft Data Quality Services, you can also consider the following products

RingLead - RingLead offers a complete end-to-end suite of products to clean, protect, and enhance company and contact information.

Oracle Data Quality - Overview of Oracle Enterprise Data Quality

WinPure Clean & Match - WinPure Clean & Match is the worlds best data cleansing & data matching software for sophisticated matching, cleansing and deduplication.

Analytics Canvas - Analytics Canvas is a data management platform with a specific focus on Google data tools, enabling self-serve data preparation and automation for those working with Analytics, Ads, Search Console, Sheets, BigQuery, Data Studio and more.

SAS Data Quality - SAS Data Quality gives you a single interface to manage the entire data quality life cycle: profiling, standardizing, matching and monitoring.

InfoSphere - IBM InfoSphere Information Server is a market-leading data integration platform which includes a family of products that enable you to understand, cleanse, monitor, transform, and deliver data.

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