IBM InfoSphere Information Server vs. IBM InfoSphere QualityStage

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

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.

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

• Create rules
• Standardization and normalization of data
• Integration with DataStage

Incentivized

• 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.

• Should include all the data profiling functionality
• Better features to tune matching capability
• Include AI to automatically recommend actions to improve processes

Incentivized

• Scale of implementation
• IBM techsupport

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.

QualityStage is positioned as a world leader as a data cleaning tool, and competes face to face with PowerCenter. Particularly in Latin America we consider that QualityStage is better customized in terms of data cleaning rules for the region.

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

• Improving Data Quality
• Reducing costs due to better Data Quality
• Single view of customer / product
• Better data governance

Incentivized