Skip to main content

What is Fact Table?



                                                                                                                                                                      
Fact Table
The centralized table in a star schema is called as FACT table. A fact table typically has two types of columns: those that contain facts and those that are foreign keys to dimension tables. The primary key of a fact table is usually a composite key that is made up of all of its foreign keys.
In the example fig 1.6 "Sales Dollar" is a fact(measure) and it can be added across several dimensions. Fact tables store different types of measures like additive, non additive and semi additive measures.
Measure Types
• Additive - Measures that can be added across all dimensions.
• Non Additive - Measures that cannot be added across all dimensions.
• Semi Additive - Measures that can be added across few dimensions and not with others.
A fact table might contain either detail level facts or facts that have been aggregated (fact tables that contain aggregated facts are often instead called summary tables).
In the real world, it is possible to have a fact table that contains no measures or facts. These tables are called as Factless Fact tables.
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.(region name, branch name, region name).
• Determine the lowest level of summary in a fact table (sales dollar).
for a product in a year within a location sold or serviced by an employee

Comments

Post a Comment

Popular posts from this blog

CMN_1650 A duplicate row was attempted to be inserted into a dynamic lookup cache Dynamic lookup error.

Scenario: I have 2 ports going through a dynamic lookup, and then to a router. In the router it is a simple case of inserting new target rows (NewRowLookup=1) or rejecting existing rows (NewRowLookup=0). However, when I run the session I'm getting the error: "CMN_1650 A duplicate row was attempted to be inserted into a dynamic lookup cache Dynamic lookup error. The dynamic lookup cache only supports unique condition keys." I thought that I was bringing through duplicate values so I put a distinct on the SQ. There is also a not null filter on both ports. However, whilst investigating the initial error that is logged for a specific pair of values from the source, there is only 1 set of them (no duplicates). The pair exists on the target so surely should just return from the dynamic lookup newrowlookup=0. Is this some kind of persistent data in the cache that is causing this to think that it is duplicate data? I haven't got the persistent cache or...
Post a Comment
Read more

SQL Transformation with examples

============================================================================================= SQL Transformation with examples   Use : SQL Transformation is a connected transformation used to process SQL queries in the midstream of a pipeline . We can insert, update, delete and retrieve rows from the database at run time using the SQL transformation. Use SQL transformation in script mode to run DDL (data definition language) statements like creating or dropping the tables. The following SQL statements can be used in the SQL transformation. Data Definition Statements (CREATE, ALTER, DROP, TRUNCATE, RENAME) DATA MANIPULATION statements (INSERT, UPDATE, DELETE, MERGE) DATA Retrieval Statement (SELECT) DATA Control Language Statements (GRANT, REVOKE) Transaction Control Statements (COMMIT, ROLLBACK) Scenario: Let’s say we want to create a temporary table in mapping while workflow is running for some intermediate calculation. We can use SQL transformat...
1 comment
Read more

Load the session statistics such as Session Start & End Time, Success Rows, Failed Rows and Rejected Rows etc. into a database table for audit/log purpose.

                                                                                                                                                                     ...
Post a Comment
Read more