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Data-Oriented B2B Application Integration

Data-Oriented B2B Application Integration. Chapter 2 Sungchul Hong. Data-Oriented B2B Application Integration. Data-oriented B2B application integration allows for data to be moved between data stores. Data share among data stores with trading partners. Complex database technology

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Data-Oriented B2B Application Integration

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  1. Data-Oriented B2B Application Integration Chapter 2 Sungchul Hong

  2. Data-Oriented B2B Application Integration • Data-oriented B2B application integration allows for data to be moved between data stores. • Data share among data stores with trading partners. • Complex database technology • Updating database and integrity issues. • Complex and complicated mosaic of various database technologies • Data compatibility, and semantics

  3. Data Access • End-run around application logic and user interfaces to extract or load data directly into the database. • Access and move information between databases • Oracle & Sybase • Decouple the database from the application and interface. • Tightly coupled with the application logic. • Simplicity and speed-to-market advantages (business logic)

  4. Coupling v.s. Cohesion • Coupling • Binding of applications together in such a way that they are dependent on each other, sharing methods, interfaces, and data. • Common business process reusability, distributed objects • Cohesion • The act or state of sticking together. • Logical agreement • Applications and databases cohesively integrated are independent from one another. • flexibility

  5. XML and Data-Movement • Standards for data-movement and repository • A unified look at data that trading partners need. • Provides context and meaning to data • Introduce and define a new type of document. • Meta data can represent abstract concepts • Encode existing metadata standard

  6. Example • An inventory control system uses • PowerBuilder • Oracle • ERP with Informix relational database • Data-movement requirement is light • Changing ERP is not an option (supplier will not agree on it) • Solution: Data-oriented B2B integration and the Internet

  7. Example • Move data from the Oracle to Informix • Understand the metadata for each database • (09/17/62)(Linthicum)(Dave)  (Semptember 17, 1962)(David Linthicum) • Sale  create event  Supplier’s ERP • Frequency of data-movement • Method of moving data • Database replication software, message broker, utility • Database replication and integration solution • Oracle  middle-tier (extract, reformatted, updated) Informix • Application logic is bypassed

  8. Data-Oriented B2B Application Integration • Database-to-database B2B application integration • Federated database B2B application integration.

  9. Database-to-Database B2B Application Integration • Allows us to share information at the database level. • One-to-one, one-to-many, many-to-many connections • Database middleware & database replication software • Message broker • Basic replication solution • Maintain basic schema information • Replication and transformation

  10. Advantages &Disadvantages • Simplicity • Dealing with application information at the data level. • Too many applications that bind the application logic to the data.  need to change application interface. • SAP R/3 updates the database using its interface.

  11. Federated Database B2B Application Integration • It works at the database level. • Creates a single virtual database model that allows developers to use various brands, models, and schemas to access any number of databases. • The virtual database is mapped to any number of connected physical databases.

  12. Advantages & Disadvantages • It relies on middleware to share information between applications. • Middleware hides the differences in the integrated databases from the other applications. • It’s not true integration. • It is difficult to create common schema.

  13. Data Source • Most databases today use the relational database model. • However there are other types of databases. • Legacy system. • IDMS, IMS, VSAM, ISAM, COBOL files • When dealing with different databases, we must understand • Data model • Nature of the database

  14. Relational Data Model • Dominant database • Use database as • Storage mechanism • Location for application processing. • Relatively small risk. • Oracle, Sybase, and Informix

  15. Object-Oriented Data Model • Fail to substitute relational model • Relational models extend to object-oriented model. • OODB model is a better fit for certain applications, including XML. • It can handle complicated mission critical data or binary data. • Contains both data and methods.

  16. Multidimensional Data Model • It supports online analytical processing (OLAP) or data mining. • Data warehousing • Huge capacity. • Cube model • Cube contains all the possible intersections • Slicing and dicing

  17. Other Data Storage Models • Indexed Sequential Access Method(ISAM) • Virtual sequential Access Method (VSAM) • Conference on Data Systems Language (CODASYL) (a standard) • Adabas (Adaptable Database) • Supports various database models in a single database.

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