Contents
How do you create a fact table in data warehouse?
Steps in designing Fact Table:
- Identify a business process for analysis(like sales).
- Identify measures or facts (sales dollar).
- Identify dimensions for facts(product dimension, location dimension, time dimension, organization dimension).
- List the columns that describe each dimension.
What is difference between fact table and dimension table?
The fact table contains business facts (or measures), and foreign keys which refer to candidate keys (normally primary keys) in the dimension tables. Contrary to fact tables, dimension tables contain descriptive attributes (or fields) that are typically textual fields (or discrete numbers that behave like text).
What are the types of fact tables?
There are three types of fact tables:
- Transaction Fact Table. The transaction fact table is a basic approach to operate the businesses.
- Snapshot Fact Table. The snapshot fact table describes the state of things at a particular time and contains many semi-additive and non-additive facts.
- Accumulated Fact Sheet.
What are the different types of data warehouse design?
there is one
What is the approximate size of a data warehouse?
Data warehouse contains all historical data so the database size is large.Approximate size of data warehouse is greater than 100 GB . Data mart contains data with only one business area so the size of database is smaller than data warehouse. Data warehouse data comes from multiple heterogeneous data sources.
What is measure in data warehouse?
Jump to navigation Jump to search. In a data warehouse, a measure is a property on which calculations (e.g., sum, count, average, minimum, maximum) can be made.
What is data granularity in a data warehouse?
Granularity refers to the level of detail of the data stored fact tables in a data warehouse. Higher granularity refers to detailed data that is at or near the transaction level (atomic level). Low granularity refers to data that is summarized or aggregated, usually from the atomic level data.