A data warehouse can be built using a top-down approach, a bottom-up approach, or a combination of both.
Top Down Approach
- The top-down approach starts with the overall design and
- It is useful in cases where the technology is mature and well known, and where the business problems that must be solved are clear and well understood.
Bottom up Approach
- The bottom-up approach starts with experiments and
- This is useful in the early stage of business modeling and technology
- It allows an organization to move forward at considerably less expense and to evaluate the benefits of the technology before making significant
- In the combined approach, an organization can exploit the planned and strategic nature of the top-down approach while retaining the rapid implementation and opportunistic application of the bottom-up
The warehouse design process consists of the following steps
- Choose a business process to model, for example, orders, invoices, shipments, inventory, account administration, sales, or the general
- If the business process is organizational and involves multiple complex object collections, a data warehouse model should be followed. However, if the process is departmental and focuses on the analysis of one kind of business process, a data mart model should be
- Choose the grain of the business process. The grain is the fundamental, atomic level of data to be represented in the fact table for this process, for example, individual transactions, individual daily snapshots, and so
- Choose the dimensions that will apply to each fact table record. Typical dimensions are time, item, customer, supplier, warehouse, transaction type, and
- Choose the measures that will populate each fact table record. Typical measures are numeric additive quantities like dollars sold and units