SAS DataFlux vs Informatica Data Quality

• dfPower Studio connects to virtually any data source, and any dfPower Studio user in any department can use dfPower Studio to profile, cleanse, integrate, enrich, monitor, and otherwise improve data quality throughout the enterprise. dfPower Architect, an innovative job flow builder, enables users to build complex management workflows quickly and logically.
• DataFlux Integration Server supports the ability to run batch dfPower Studio jobs in a client/server environment.
• DataFlux Integration Server for SAS additionally enables allows SAS programs to invoke DataFlux batch jobs from a SAS program and allows SAS programs to call a business service that was designed in the dfPower Studio client environment.

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• The matching algorithms in IDQ are very powerful if you understand the different types that they offer (e.g., Hamming Distance, Jaro, Bigram, etc..). We had to play around with it to see which best suit our own needs of identifying and eliminating duplicate customers. Setting up the whole process (e.g., creating the KeyGenerator Transformation, setting up the matching threshold, etc..) can be somewhat time consuming and a challenge if you don't first standardize your data.
• The integration with PowerCenter is great if you have both. You can either import your mappings directly to PowerCenter or to an XML file. The only downside is that some of the transformations are unique to IDQ, so you are not really able to edit them once in PowerCenter.
• The standardizer transformation was key in helping us standardize our customer data (e.g., names, addresses, etc..). It was helpful due to having create a reference table containing the standardized value and the associated unstandardized values. What was great was that if you used Informatica Analyst, a business analyst could login and correct any of the values.

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• DataFlux handled all of our data integration needs. It could be considered pricey when compared to Microsoft's bundled SSIS product.

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• Several partnerships diminishing the value of technologies
• Unable to get list of objects from Repository (like sources & targets) that don't have any dependency
• Scheduling: The built-in scheduling tool has many constraints such as handling Unix/VB scripts etc. Most enterprises use third party tools for this.

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• Complex data integration.
• SAS integration.

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• Integration with tools like PowerCenter helped faster delivery of product, and at the same time conversion
• Reduce overall project cost due to bad data , bad quality, exceptions identified nearing go-live and post production
• Employee efficiency is increased exponentially due to more automated, customized tool

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