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Data warehousingIn addition to designing and implementing HCL OneDB™ dimensional databases, you can use tools to create data warehouse applications and optimize your data warehouse queries.
Dimensional databasesThe HCL OneDB™ Data Warehouse Guide provides information to help you design, implement, and manage dimensional databases, and describes the tools that you can use to create data warehouses and optimize your data warehouse queries.
Design a dimensional data modelTo build a dimensional database, you start by designing a dimensional data model for your business.
Building a dimensional data model
Determine the granularity of the fact tableAfter you gather all the relevant information about the subject area, the next step in the design process is to determine the granularity of the fact table.
Use the business process to determine the granularity
Customer by product by district by day level granularityCustomer-buying trends always occur over time, so the granularity of the fact table must include a time component.

Customer by product by district by day level granularity

Customer-buying trends always occur over time, so the granularity of the fact table must include a time component.

Suppose your organization decides to create reports by week, accounting period, month, quarter, or year. At the lowest level, you probably want to choose a base granularity of day. This granularity allows your business to compare sales on Tuesdays with sales on Fridays, compare sales for the first day of each month, and so forth. The granularity of the fact table is now complete.

The decision to choose a granularity of day means that each record in the time dimension table represents a day. In terms of the storage requirements, even 10 years of daily data is only about 3,650 records, which is a relatively small dimension table.

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