IBM InfoSphere Information Server vs. Informatica Cloud Data Quality

You can use infosphere: -If you have multiple targets and source systems and they are different than each other. -If your infostructure is so big and unplaned well so you can't find what you want to see. -If your databases not so strong to process your data

Incentivized

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

• It is very strong to make transformations/data derivations
• It is very easy to connect to various external data sources. It has an interface (stages) for each connection that simplifies the task
• It is a stable platform. And that parallelism helps make it fast for loading, if the process is well designed

• 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

• Lack of a strong web development environment.
• Metadata propagation in Jobs is somewhat complex.
• The possibility to develop jobs in Parallel and/or Server Engines is confusing.

• 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.

• Scale of implementation
• IBM techsupport

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.

Easy to use not only for developers but also business users

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 particularly believe that Information Server, especially DataStage, is superior in many aspects to the Oracle Data Integrator tool. Several market analysts such as Gartner and / or Forrester better position DataStage on the Oracle solution.

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

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

Incentivized

• Information Server can positively impact the costs of companies by increasing the productivity of development and therefore reduce their time and costs. It is estimated that DataStage can increase a developer's productivity by 40% on average.
• Better data governance
• Improve data quality and reduce bad data impacts

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