1. Migration to the Architected Environment

2. A migration plan The beginning point for the migration plan is a corporate data model. This model represents the information needs of the corporation. The corporate data model may be built internally, or it may have been generated from a generic data model

3. A migration plan (cont’d) The corporate data model needs to identify ( at minimum!) the following: –Major subjects of the corporation –Definition of the major subjects of the corporation –Relationships between the major subjects –Groupings of keys and attributes that more fully represent the major subjects, including the following: Attributes of the major subjects Keys of the major subjects Repeating groups of keys and attributes –Connections between major subject areas –Subtyping relationships

6. A migration plan (cont’d) As a rule, the corporate data model identifies corporate information at a high level. From the corporate data model a lower-level model is built. The lower-level model identifies details that have been glossed over by the corporate data model. This mid-level model is built from the subject area at a time. It is not built on an all-at-once basis because such doing so takes so long

7. A migration plan (cont’d) Some reasons for excluding derived data and DSS data from the corporate data –Derived data and DSS data change frequently –These forms of data are created from atomic data –They frequently are deleted altogether –There are many variations in the creation of derived data and DSS data

8. A migration plan (cont’d) Defining the System of record The system of record is defined in terms of the corporation’s existing system The system of record is nothing more than the identification of the ‘best’ data the corporation has that resides in the legacy operational or in the web-based e-business environment The data model is used as a benchmark for determining what the best data is.

9. A migration plan (cont’d) Defining the System of record The ‘best’ source of existing data or data found in the web-based e-business environment is determined by the following criteria: What data in the existing systems or web-based e- business environment: –Is the most complete –Is the most timely –Is the most accurate –Is the closest to the source of entry –Is the most closely to the structure of the data model? In terms of keys? In terms of attributes? In terms of groupings of data attributes

10. A migration plan (cont’d) Defining the System of record A short list of technological changes includes the following: –A change in DBMS –A change in operating systems –The need to merge data from different DBMSs and operating systems –The capture of the web-based data in the web logs –A change in basic data formats

11. A migration plan (cont’d) Defining the System of record The next step: Design the data warehouse

14. A migration plan (cont’d) Defining the System of record Principally, the following needs to be done: –An element of time needs to be added –All purely operational data needs to be eliminated –Referential Integrity relationships need to be turned into artifacts –Derived data that is frequently needed is added to the design

15. A migration plan (cont’d) Defining the System of record The data warehouse, once designed, is organized by subject area. Typical subject areas are as follows: –Customer –Product –Sale –Account –Activity –Shipment

16. A migration plan (cont’d) Defining the System of record The next step: Design and build the interfaces between the system of record-in the operational environment and the data warehouse The interfaces populate the data warehouse on a regular basis.

17. A migration plan (cont’d) Defining the System of record A word of caution: If you wait for existing systems to be cleaned up, you will never build a data warehouse. One observation worthwhile at this point relates to the frequency of refreshment of data into the data warehouse. As a rule, data warehouse data should be refreshed no more frequently than every 24 hours.

18. Strategic Considerations

21. Methodology and Migration

23. A data-driven development methodology Why have methodologies been disappointing? –Methodologies generally show a flat, linear flow of activities –Methodologies usually show activities as occurring once and only once. –Methodologies usually describe a prescribed set of activities to be done –Methodologies often tell how to do something, not what needs to be done –Methodologies often do not distinguish between the sizes of the systems being develop under the methodology –Methodologies often mix project management concerns with design/development activities to be done –And many more

24. Data-Driven Methodology A data-driven methodology does not take an application-by-application approach to the development of systems