IBM InfoSphere Information Server vs. Melissa Data Quality Suite

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

The platform is best suited for detailed exploration and filtering that allow users to examine the specific records
that pass or fail a criterion and how they might relate to each other. It also assist in seeing past jobs and compare how quality has changed, providing
more context than just point values.

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

• It provides ability to profile, discover, and validate data quality.
• It allows to drill down into larger amounts of data.
• It automatically suggests possible quality rules based on a statistical profile of the data.

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.

• It can expand connectivity to apply adaptive data quality rules to any data source.
• It can employing more advanced transformation techniques to transform data for specific formats.
• It can further continue on its existing capabilities like providing more enriched data curation.

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.

• 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