Data Warehouse Implementation
Organization-wide information system development is subject to many constraints. Some of the constraints are based on available funding. Others are a function of management’s view of the role played by an IS department and of the extent and depth of the information requirements. Add the constraints imposed by corporate culture, and you understand why no single formula can describe perfect data warehouse development. Therefore, rather than proposing a single data warehouse design and implementation methodology. The following are the few factors that appear to be common to data warehousing.
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I. A Company-Wide Effort That Requires User Involvement:
Designing a data warehouse means being given an opportunity to help develop an integrated data model that captures the data that are considered to be essential to the organization, from both end-user and business perspectives. Data warehouse data cross departmental lines and geographical boundaries. Because the data warehouse represents an attempt to model all of the organization’s data. Building the perfect data warehouse is not just a matter of knowing how to create a star schema; it requires managerial skills to deal with conflict resolution, mediation, and arbitration. In short, the designer must:
• Involve end users in the process.
• Secure end users’ commitment from the beginning.
• Solicit continuous end-user feedback.
• Manage end-user expectations.
• Establish procedures for conflict resolution.
II. Satisfy the Trilogy: Data, Analysis, and Users:
Great managerial skills are not, of course, solely sufficient. The technical aspects of the data warehouse must be addressed as well. The old adage of input-process-output repeats itself here. The data warehouse designer must satisfy:
• Data integration and loading criteria.
• Data analysis capabilities with acceptable query performance.
• End-user data analysis needs.
III. Apply Database Design Procedures:
• The database life cycle and the database design process must be adapted to fit the data warehouse requirements. Developing a data warehouse is a company-wide effort that requires many resources: human, financial, and technical.
• The sheer and often mind-boggling quantity of decision support data is likely to require the latest hardware and software—that is, advanced computers with multiple processors, advanced database systems, and large capacity storage units.
• Very detailed procedures are necessary to orchestrate the flow of data from the operational databases to the data warehouse. Data flow control includes data extraction, validation, and integration.
• To implement and support the data warehouse architecture, you also need people with advanced database design, software integration, and management skills.
The following figure depicts a simplified process for implementing the data warehouse.
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