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Rational Data Architect skills series, Part 1: Access and integrate enterprise metadata with Rational Data Architect

Farnaz Erfan (erfan@us.ibm.com), Staff Software Engineer, IBM
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Farnaz Erfan is the team lead for WebSphere Information Integrator federation administration tooling. She has more than six years experience with federation tooling, including health monitoring, statistics, and server discovery. Farnaz graduated from Purdue University with a Bachelor of Science degree in Computer Science and joined IBM in June 2000. Contact her at erfan@us.ibm.com.
Mary Roth (torkroth@us.ibm.com), Solutions Architect, IBM
Mary Roth
Mary Roth is a senior technical staff member with the WebSphere Information Integration Solutions (WIIS) team. She has led several efforts in WIIS, including heterogeneous federation, discovery-driven integration design, and mapping technology for information integration. Mary was previously at the IBM Almaden Research Center, where she contributed key advances in heterogeneous data integration techniques and federated query optimization. Mary has a B.S. degree in Mathematics from Marquette University and an M.S. degree in Computer Sciences from the University of Wisconsin. Contact her at torkroth@us.ibm.com.

Summary:  Data integration in an enterprise of data sources is one of the most common requirements of any database shop. Users need on demand integrated access to a variety of diverse data sources, such as traditional data assets like Excel spreadsheets and legacy data, to new and emerging technologies such as XML data stores. IBM® WebSphere® Information Integrator provides a single interface that allows end users and database administrators to virtually and transparently access a wide variety of these data sources. IBM Rational® Data Architect (Data Architect) works with WebSphere Information Integrator to give data architects and application developers the ability to discover, model, visualize, relate, and develop data assets across distributed and diverse data sources. In this tutorial, you follow a simple scenario to learn how Rational Data Architect can be used to provide a modeling and design tool to create a unified, virtual view across heterogeneous data sources.

View more content in this series

Date:  25 Jul 2006
Level:  Intermediate
PDF:  A4 and Letter (3361 KB | 45 pages)Get Adobe® Reader®

Activity:  13744 views
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Reverse engineering physical data from a database

To map live database schemas to a new model, you need to place them in your data design project. To increase the speed of this process, you can use filters on your remote schemas and remote tables, as follows.

  1. In the Database Explorer, right-click on the Remote Schemas folder under the SANTA_CLARA_COUNTY server and select Filter to open a Filter window.
  2. Uncheck Disable filter, and specify Selection to include the Oracle schema in which you have created your Oracle tables. In this case it is J15USER1, as shown in Figure 17.
  3. Select Finish.

Figure 17. Filtering remote Oracle schemas
Figure 17. Filtering remote Oracle schemas

After you filter the remote schema, use the same steps on the Remote Tables folder to filter the seven tables that you created for SANTA_CLARA_COUNTY database in Prerequisites. These tables are BOOK, BOOK_AUTHORS, BOOK_COPIES, BOOK_LOANS, BORROWER, BRANCH, and PUBLISHER, as shown in Figure 18.


Figure 18. Filtering remote Oracle tables
Figure 18. Filtering remote Oracle tables

Repeat the same steps for remote tables and remote schemas under the LIBRARY server. Filter on remote schema SCHOOL and remote tables BOOK, BOOK_AUTHORS, and LOCATION.

Drag both LIBRARY and SANTA_CLARA_COUNTY servers from the Defined Remote Servers folder in the Database Explorer to the New Library System Data Design Project in the Data Project Explorer.

You will notice that three new files with a .dbm extension are added to the Design Project: FEDERATE.dbm, LIBRARY.dbm, and SANTA_CLARA_COUNTY.dbm.

If you expand LIBRARY.dbm and SANTA_CLARA_COUNTY.dbm, you will see the tables that you created during Prerequisites. These tables are now model objects that were extracted from reverse engineering the two physical databases, as shown in Figure 19.


Figure 19. Models extracted from reverse engineering physical databases
Models that extracted from reverse engineering physical databases

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