Fact Table

Fact Table

Type of Fact-

1-Additive- Additive facts are facts that can be summed through all of the dimensions in the fact table.
2-Semi-Additive- Semi-aditive facts are that can be summed through some of the dimensions and cannot be summed through some dimensions.
3-Non-Additive- Non-additive facts are that can not be summed up for any dimensions in fact table

Factless Fact table-

A factless table is fact table which does not contains any measure. It is just an intersection of dimenstions.

Dataware Housing Concept

Data warehousing concept is a process of collecting, organizing, and managing data from different data sources to create and provide useful business insights. 

The main features of a data warehouse are as below:

• Subject Oriented- A data-ware house provides information about subject (area) of organization. like sales, marketing etc.

• Integrated- A data warehouse integrates data from different heterogeneous sources. They should not have naming conflicts and differences between values of measures.

• Non-Volatile- Non-volatile means, data should not be removed over the time. because data is used for analysis purpose.

• Time Variant- Data in data warehouse changes with time. It stores more data as time passes.

How to design a Data Warehouse?

What is Data Warehouse?

A  data warehouse is a relational database which is used for reporting and data analysis. Data warehouse is a main component of BI.

Data warehouse can be defined under two main concept-

According to Bill Inmon-

A data warehouse is subject-oriented,integrated,time-variant and non-volatile collection of data in support of management's decision-making process.

According to Ralph Kimball-

A data warehouse is a copy of transaction data specifically structured for query and analysis.

Difference between detail filter and summary filter

Filters are used to emphasize the important information and filter out what is unnecessary. You can apply a filter to a report to change the focus of the report.

Detail filter:-

• Detail filter is used to filter detail-level data within a report. A detail filter applies one or more specified conditions to each row of data. If conditions are true for a row, data in the row is retrieved and appears in the report. If a condition is not true, then row is not retrieved and it is not retrieved in the report.
• Detail filters can apply to each and every record in the database.
• Detail filter comes under the where clause.
• In detail filter you have two options while using it:

Before auto aggregation or after auto aggregation i.e. before the data is brought into the cache or after the data has been brought into the cache.

If you add set the property as before auto aggregation filter will be applied to where clause otherwise filter is applied in having

Summary filter:

• A summary filter is used to filter summary-level data in a report. Before you create a summary filter,  you must calculate the summary level data items that you want to use in the filter.
• A summary filter can apply to summary level data.
• Summary filter comes under having clause.
• Summary filters don't have the option before auto-aggregation or after aggregation.