Informatica Cloud Data Quality vs. SAP Information Steward

We used Informatica Data Quality to measure the "Data Quality Score" of internal and external reports at my company. Business users set up data profiling and prepared detailed analysis documents for business analysts. and developers developed Data Quality Mapplets for other IT teams to import their Informatica Power Center repositories. Results are stored in a centralized data quality space and then reported and summarized to related business users in detailed ways. At the end of each project, we are now able to place a "Data Quality Score" watermark score on each report involved.

Incentivized

In data conversion scenarios, the tool can be used for data profiling, data quality and data verification jobs. However, implementation depends on what implementation strategy or approach the company is adopting. In real-time scenarios, the tool can be used for generating data profiling and data quality reports as well. Business rules for data quality checks can be built into the tool and can be assigned to end or business users.

Incentivized

• Watch the data real time- After creating the job the data quality engine checks and run the custom rules creating a navigation window at the bottom for review and accessing the data right away.
• Character Set Mapping
• Makes sense of our own data, which in turn gives us confidence that we can provide to the end users. IDQ helped us with erroneous data in accounting and HR for accurate and immaculate reports

• Data Profiling
• Data Quality Monitoring
• Dashboards

Incentivized

• 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.

• More real-time integration scenarios needed.
• Needs more generic standard content for metadata management.
• The user interface can be more intuitive based on AI.

Incentivized

I gave a rating of 8 due to the fact that we use Informatica for both our data quality product and ETL product. Having both integrated makes it so much easier. Microsoft had a similar product of finding duplicates, but at the time it didn't seem mature enough. The usability also in IDQ was pretty easy to navigate and use.

Out of the box solution

Incentivized

Easy to use not only for developers but also business users

Incentivized

It provides out of box solution for information management at organisation level

Incentivized

The application works well except an occasional error out while using the system. It usually gets fixed when restarting the Infa server

Incentivized

Performance works just fine. It was able to load 200+ business terms, 150+ DQ automation, etc. very well.

Incentivized

I believe many features from SAP Information Steward are available in other SAP products as well hence it is more confusing for business or customers to do the right selection. Moreover SAP strategy is not very clear for this particular product hence often we are confused while exploring more related scenarios

Incentivized

Ready recknoer tools that act as reference are missing that can help to formulate ;Decision Driven Framework' for various strategic decesions

Incentivized

Informatica Data Quality has a wide range of cleansing features, that are detailed, professional, and accurate in scaling down the required database. Further, Informatica Data Quality ensures there is proper collaboration, and this fosters businesses to have the freedom of working closely with several programs. Finally, Informatica Data Quality design is authentic and allows personalization.

Incentivized

In the case of this organization, Information Steward was part of a suite from SAP together with Data Services and SAP Master Data Governance. In terms of the overall package it was worth it for the company. Informatica cost was higher and the overall benefit from SAP package was the key decision point.

Incentivized

Scalability works as expected and it is truly an enterprise system.

Incentivized

• 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

• Improved data flaws
• Catching mistakes in data
• Reduced technical errors

Incentivized