1.Top-Down Approach
The top-down approach is usually business driven, meaning that the data warehouse is a corporate directive. It has full support, business and financial, from senior management of a company, who has a clear understanding of what to expect from a data warehouse. The hardest part of top-down methodology is that all business organizations have to agree on a common set of Key Performance Indicators and other analytical key measurements needed to make tactical and strategic business decisions.The benefit of this approach is that you have full corporate-level sponsorship to implement a data warehouse. However, in a corporate-wide initiative, the initial scope of what to implement can be very broad. Also, it will take a long time before end users actually see the value of a data warehouse.
Bottom-Up Approach
The bottom-up approach has been the most common way of implementing data marts. In this case, either a business manager or a department manager steps up to launch a data warehouse project with full financial support. This approach has several advantages: limited scope of what to implement, control over what to analyze, and easier rollout at a department level.
The problem with this approach is that the implementation scope is very limited. The implementation is not visible at the corporate level and carries with it typical data-mart-related issues, such as inconsistent enterprise-wide data definitions and supporting technologies.
Hybrid Approach-SAP Approach
SAP proposes a hybrid approach for BW that takes advantage of the top-down and bottom-up methodologies.The corporate directive is one key feature of the top-down methodology. Here individual department business drivers can exploit SAP BW technology to implement a specific, business-focused data mart solution .These data marts do not become obsolete when a corporate-wide initiative is launched; instead, they become an integral component of the corporate information supply chain. The SAP Accelerated SAP (ASAP) methodology for BW is a hybrid of the top-down and bottom-up approaches in implementing data warehouses.
Initially, we have to limit the scope of an SAP BW project to one of the common business process areas, such as Sales and Distribution, Financial Accounting and Material Management, or Human Resources. Draft a project charter that articulates the value of SAP BW in terms of its data analysis flexibility, speed, manageability, and information delivery. Present a case for SAP BW to your senior management. Get commitment from a high-level business sponsor before doing further SAP BW project-detailed scoping.
The SAP BW project scope outlines what data analysis functionality will be delivered.Data analysis and reporting needs are classified in the following groups:
Operational Reporting : Requires real-time state-of-business operations, such as overdue orders, orders on hold, or released sales orders at the time of inquiry. These types of inquiries are very much transaction-centric.
Management Reporting and Analysis : Business managers or business analysts define what that time period should be and for what data set. This could be daily, weekly, or monthly.the management reporting and data analysis are subject-centric, such as sales, finance, and human resources.
Enterprise-Wide Reporting: Covers a broad range of data analysis needs across several subject areas spanning several years of data. Here, analysts and data-mining experts explore large amounts of data for strategic planning.(5.1)
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