IBM InfoSphere QualityStage

IBM InfoSphere QualityStage

About TrustRadius Scoring
Score 9.0 out of 100
IBM InfoSphere QualityStage

Overview

What is IBM InfoSphere QualityStage?

IBM InfoSphere QualityStage is a data quality offering from IBM.
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Recent Reviews

Quality Stage

9 out of 10
November 28, 2018
QS is used in the service area. I have implemented it in companies where your business is data. And with it, we have achieved very good …
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Reviewer Pros & Cons

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Pricing

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What is IBM InfoSphere QualityStage?

IBM InfoSphere QualityStage is a data quality offering from IBM.

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting / Integration Services

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Product Details

What is IBM InfoSphere QualityStage?

IBM InfoSphere QualityStage is a data quality offering from IBM.

IBM InfoSphere QualityStage Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Frequently Asked Questions

IBM InfoSphere QualityStage is a data quality offering from IBM.

Reviewers rate Data source connectivity and Data profiling and Master data management (MDM) integration highest, with a score of 9.

The most common users of IBM InfoSphere QualityStage are from Mid-sized Companies (51-1,000 employees) and the Civil Engineering industry.
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Comparisons

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Reviews and Ratings

 (5)

Reviews

(1-3 of 3)
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Wendy Durf | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Effectively integrating with DataStage and great management of data quality and through the IBM InfoSphere QualityStage is an easy process identifying various revenue opportunities. Easy rules creation platform which offers the best Cloud functionalities enabling effective management of all the companies information and the activities monitoring functions and also easy data pulling via Cloud services.
  • Effective data quality enhancement product.
  • Deep proofing of multiple data.
  • Excellent for easy identification of revenue opportunity.
  • The implementation not easy at all.
  • The learning curve is very long.
  • Multiple Cloud data management, especially to the new users.
The best, flexible and powerful Cloud data classification and Cloud data management software and its capabilities are effective and very protective IBM solutions. Easy interface setting and its integration support are functional, allowing easy complex data pulling and the tool scalability and features performance, as well as data quality improvement, are the effective capabilities provided by this IBM platform.
November 28, 2018

Quality Stage

Score 9 out of 10
Vetted Review
Verified User
QS is used in the service area. I have implemented it in companies where your business is data. And with it, we have achieved very good results.
Addresses errors with address standardization, user unification, data cleansing of phones, addresses, etc.
  • Create rules
  • Standardization and normalization of data
  • Integration with DataStage
  • You need to learn the language of pattern to create rules
  • Must be thorough for the definition of the rule, because it can give you unexpected results
Good for issues with data quality, and instances where you need to add controls and rules to load the data. Also if you have a large amount of data.
Gonzalo Angeleri | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
QualityStage is used as a corporate tool for profiling and data cleaning. It is used especially in the data warehousing area, but also in other areas such as marketing and sales. QualityStage allows you to understand the level of data quality of the original systems, and prepare the data to deliver them with the required quality level.
  • Worldwide address and name rules for data standardization
  • Integration with other tools like DataStage
  • Graphical interfase to develop processes
  • Performance and scalability
  • Should include all the data profiling functionality
  • Better features to tune matching capability
  • Include AI to automatically recommend actions to improve processes
Standardization of data using rules for names and addresses. Possibility of building our own rules to standardize other data. Contruction of complex rules of matching and consolidation of data. Native integration with ETL tools and data governance.
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