The biggest difference is IDQ is the engine you need to actually perform data quality improvement (ie. cleansing, matching, standardization, etc.). IDQ does have some of the capabilites of IDE included, such as column level profiling and some scorecarding but when you want to understand structural issues across your environment, the full edition of IDE is required allowing you to do cross table analysis, foreign key/primary key inference and the like. In our upcoming release we will be introducing additional capabilites to further enhance what IDE can do, namely adding functionality in the area of discovery.
As for the user interface, both IDQ and IDE do indeed share the same interface tool. There are two possible ways to interact with each, namely the Developer Tool or the Analyst Tool. The first is an Eclipse based interface designed for developers while the second is a browser based, easier to use tool designed for analysts and business oriented users.
Hope this helps.
Hi Suman. Since Informatica truly unified data quality and data profiling/discovery with the 9.0 release back in 2009, this has been a common question. While ultimately users benefit via collaboration and reuse of core artifacts from a common architecture and client tools, differentiating IDE vs. IDQ is a question that does come up.
Let me summarize some of the commonalities shared between both IDE and IDQ, followed by differences:
Clients common between both IDE and IDQ:
- Informatica Developer client
- Informatica Analyst (browser client for profiling, validating DQ rules, scorecarding data, managing reference data, etc.)
Functionality examples common between IDE and IDQ (i.e. you can use the following if you have IDE or IDQ):
- Column Profiling
- Rule Profiling (inline validation of DQ rules within profiles)
- Reference Table Management
- Midstream profiling (profiling at any point within a mapping)
- Join validation profiling
- ETL transformations (lookup, joiner, filter, expression, etc.)
Functionality examples that are specific to IDQ and IDE respectively:
- Ability to leverage Data Quality transforms (e.g. Matching, Address Validation, Parsing, Standardization, etc.)
- Such transforms are not usable if only have IDE (and not IDQ)
- Data Discovery (ability to discover data domains and sensitive data)
- Structural Profiling (e.g. Primary Key Inference, Functional Dependency, Foreign Key Inference, Overlap Discovery, etc.)
- Such Discovery and Structural profiling are not usable if only have IDQ (and not IDE)