Data Architecture: The Information Paradigm |
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Page 183
... architecture . □ Close work with the end users to ensure that primitive data is providing a firm foundation for derived processing and to determine when private end user data turns into public data . In addition , the data architect ...
... architecture . □ Close work with the end users to ensure that primitive data is providing a firm foundation for derived processing and to determine when private end user data turns into public data . In addition , the data architect ...
Page 187
... data architecture ( i.e. , what data structure design is needed when ) . 2. Provide an estimate of when corporate databases will be populated and when the corporate data is a responsibility of the application . 3. Provide the code ...
... data architecture ( i.e. , what data structure design is needed when ) . 2. Provide an estimate of when corporate databases will be populated and when the corporate data is a responsibility of the application . 3. Provide the code ...
Page
... Data Architecture first appeared , much has changed in systems planning . IBM now shares Inmon's vision and recently announced Data Warehouse , an architecture to address enterprise - wide data access . In this second edition , Inmon ...
... Data Architecture first appeared , much has changed in systems planning . IBM now shares Inmon's vision and recently announced Data Warehouse , an architecture to address enterprise - wide data access . In this second edition , Inmon ...
Contents
The Information ParadigmEvolution | 37 |
The Information ParadigmTechnical Foundations | 63 |
Conceptual Foundations of the Information Paradigm | 95 |
Copyright | |
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Common terms and phrases
4GL technology activity algorithms amount of data application architected environment archival data atomic data atomic database atomic environment atomic level balance basis budget cessing COBOL current-value data DASD data and processing data architecture data elements data model data processing DBMS decision support processing Decision Support Systems departmental level derived data detailed DSS analysis DSS data DSS environment DSS processing enterprise evolution example existing systems extract processing extracted data extracted sample foundation hardware high-performance individual level Information Engineering information paradigm integrity levels of data mainframe master files ment migration needs nonredundant normal operational data operational environment operational level operational systems organization performance personal computers personnel primitive and derived primitive data processor production projection data redundancy of data separation shown by Figure stored summarized support system system of record transaction unarchitected update usage user computing