Dimension tables contain data that describe the different characteristics, or dimensions, of a business. For example, the time dimension.
They typically store process cycle times or provide the ability to easily determine process cycle times. Since it looks like dimension, but is really in fact table and has been degenerated of its description, hence is called degenerated dimension.
One data mart might have sales through one sales channel, and a second data mart might have sales Different types of fact tables a different sales channel.
The facts inside the fact table could be of several different types 1 Additive facts -Additive facts are facts that can be summed up through all of the dimensions in the fact table.
Example is Quantity, sales amount etc. It is usually found to be conical in shape with steep sides and a pointed tip called a peak. The vegetation is thick, beautiful fruit orchards are found in the hills and it is good for crop cultivation like tea and coffee.
Ralph Kimball talks about dimension outriggers as a notable exception to the goal of building star-schema models. A diagram of a star schema resembles a star, with a fact table at the center.
For example, Month is an attribute in the Time Dimension. Typically one or more description columns maybe a short description for application dropdowns that need to show a narrow description, and a longer description for report output where wider descriptions can be used.
At some places the land may be too high, at some places very low, some areas would be lush green and certain areas are dry and barren. Example the Isthmus of Panama. The continent of Australia is an island. This chapter explains dimensional database modeling and the concepts of star schemas.
Why is it terrible. The ratio can be calculated in a data access tool for any slice of the fact table by remembering to calculate the ratio of the sums, not the sum of the ratios. However, snapshot tables are not necessarily aggregated like transactional tables, because many times the measures are non-additive or semi-additive.
It stores Purchase Cycle Line records aggregated over a preconfigured Monthly time period and product types. Snowflake schemas are ones where dimensions are spread out in a more normalized manner.
They represent the different business entities by which users wish to analyze measures. Here are some scenarios: A good example would be a trade fact in a company that brokers equity trades.
The largest archipelago in the world is Indonesia. With any participation program, you will have some people enter the program one month and drop off in a few months - so any tally or summarization of measures needs to be restricted to certain periodic intervals.
Some plateaus like the Plateau of Tibet lies between mountain ranges. Kevin has authored one book on reporting development and contributed chapters on MDX programming to a second book.
Cumulative Fact This type of fact table describes what has happened over a period of time. Structure of fact tables where transactions have different dimension types. SQL Server > SQL Server Analysis Services. (4 different types) have very different unique attributes, for example a criminal case has jail time related to it whereas a family case may have children etc.
In this partitioning strategy, the fact table is partitioned on the basis of time period. Here each time period represents a significant retention period within the business. We can reuse the partitioned tables by removing the data in them.
Partition on a Different Dimension.
The fact table can also be partitioned on the basis of. 3) Confirmed dimensions (a dimension which can be stored by multiple fact tables) 4) Slowly changing (based on period of time the dimensions will be changed a)SCD1 (most recent values in the target).
Types of Fact Tables The Kimball methodology includes 3 main types of fact tables: Transaction – the most common type of fact table, used to model a specific business process (typically) at the most granular/atomic level. Fact Tables Fact tables include keys to the dimension tables and measurable facts, which Data Analyst would need to evaluate.
For instance, a store trading automotive parts should have a fact. The following diagram shows two fact tables, namely sales and shipping.
The sales fact table is same as that in the star schema. The shipping fact table has the five dimensions, namely item_key, time_key, shipper_key, from_location, to_location.Different types of fact tables