- 1 Product Description
- 2 Known Versions
- 3 Software Pattern Summary
- 4 Platforms Supported by the Pattern
- 5 Identification
- 5.1 Software Instance Triggers
- 5.2 Software Instance Type Attributes Created
- 5.3 Simple Identification Mappings
- 6 Versioning
- 6.1 Obtaining the install root
- 6.1.1 Process
- 6.1.2 Registry
- 6.2 Obtaining the version
- 6.2.1 Registry
- 6.2.2 File
- 6.2.3 Package
- 7 Application Model Produced by Software Pattern
- 7.1 Product Architecture
- 7.2 Pattern Trigger
- 7.3 SI Depth
- 7.4 Relationship Creation
- 7.5 Discovery Server
- 7.6 Retrieving Port Information for Database
- 7.7 Discovery Engine
- 7.8 Retrieving Server Information:
- 8 Subject Matter Expertise
- 9 Testing
- 10 Information Sources
- 11 Open Issues
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- What is this?
- This is a product information page, containing details of the information that BMC Atrium Discovery gathers about a product and how it is obtained.
- Product Name
- InfoSphere Discovery
- Publisher Page
- Category
- Release
- TKU 2012-Jan-01
- Reports & Attributes
- Publisher Link
- IBM
Product Description
InfoSphere Discovery provides innovative data exploration and analysis techniques to automatically discover relationships and mappings among the structured data in the enterprise, based not on metadata but on actual values in the data itself. This value-driven analysis means that InfoSphere Discovery can detect relationships between tables and columns whose names or metadata alone do not suggest any connection. It also enables InfoSphere Discovery to identify and generate highly complex transformations that you can use to describe the locations and formats of sensitive data, describe the relationships of data elements across applications, or output as SQL or extract, transform, and load (ETL) code for use in later data transformation. Although InfoSphere Discovery performs some phases of this mapping as automated processes, it also offers a broad set of powerful and flexible tools that analysts can use to manually review, develop, refine, and finally confirm a comprehensive set of data maps. These maps can then be used as blueprints in a wide variety of data integration projects such as tracking sensitive data in the enterprise, application migration, data relationship validation, data set rationalization, and legacy ETL to commercial ETL migration.
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