fact types in data warehouse

Types Of Facts In Data Warehouse

1. Addictive Type: Enhance your IT skills and proficiency in Data Warehousing by taking up the Informatica Training.
2. Semi Addictive Fact:
3. Non-addictive fact:
4. Factless fact table: Explore Informatica Sample Resumes! Download & Edit, Get Noticed by Top Employers! Download Now!

Full Answer

What are the different types of data warehouse?

Types of Data Warehouse. There are 3 types of Data Warehousing: Enterprise Data Warehouse. Operational Data Store. Data Mart. 1. Enterprise Data Warehouse. An Enterprise data warehouse is a database that combines several functional areas of an organization in a unified way. It helps in storing data from various sources and categorizes them ...

What are the data warehouse schema types?

Types of Data Warehouses

• Host-Based Data Warehouses. Host-Based mainframe warehouses which reside on a high volume database. ...
• LAN-Based Workgroup Data Warehouses. ...
• Host-Based Single Stage (LAN) Data Warehouses. ...
• Multi-Stage Data Warehouses. ...
• Stationary Data Warehouses. ...
• Distributed Data Warehouses. ...
• Virtual Data Warehouses. ...

What are the different types of data warehouse design?

Types of Data Warehouse Schema

1. Star Schema Here are some of the basic points of star schema which are as follows: In a star schema, as the structure of a star, there is one ...
2. Snowflake Schema Here are some of the basic points of snowflake schema which are as follows: Snowflake schema acts like an extended version of a star schema. ...
3. Fact Constellation Schema or Galaxy Schema

What kind of data gets stored in data warehouses?

These types are:

• Dependent
• Independent
• Hybrid

What are the types of fact?

We can divide the Facts in to these three types.Non-Additive.Semi-Additive.Additive.

What are the 3 types of fact tables?

These are:Transaction fact tables.Periodic snapshot tables, and.Accumulating snapshot tables.

How many types of fact are there in data warehouse?

three typesThere are three types of facts: Summative facts: Summative facts are used with aggregation functions such as sum (), average (), etc. Semi summative facts: There are small numbers of quasi-summative fact aggregation functions that will apply.

What are types of fact tables in data warehouse?

Thus, a fact table consists of two types of columns. The foreign keys column allows to join with dimension tables and the measure columns contain the data that is being analyzed. A Transaction table is the most basic and fundamental view of business operations.

How many fact tables are there?

There are four types of fact tables: transaction, periodic snapshot, accumulating snapshot and factless fact tables.

Can we join 2 fact tables?

The answer for both is "Yes, you can", but then also "No, you shouldn't". Joining fact tables is a big no-no for four main reasons: 1. Fact tables tend to have several keys (FK), and each join scenario will require the use of different keys.

Which are two types of fact?

There are three types of facts:Additive: Additive facts are facts that can be summed up through all of the dimensions in the fact table.Semi-Additive: Semi-additive facts are facts that can be summed up for some of the dimensions in the fact table, but not the others.More items...

What is additive and non-additive facts?

Additive facts are those facts which give the correct result by an addition operation. Examples of such facts could be number of items sold, sales amount etc. Non-additive facts can also be added, but the addition gives incorrect results. Some examples of non-additive facts are average, discount, ratios etc.

What are additive semi-additive and non-additive facts?

Semi-additive measures can be aggregated across some dimensions, but not all dimensions. For example, measures such as head counts and inventory are considered semi-additive. Non-additive measures are measures that cannot be aggregated across any of the dimensions.

What are the types of fact and data?

Types of Facts in Data WarehouseAdditive: Additive facts are facts that can be summed up through all of the dimensions in the fact table. ... Semi-Additive: Semi-additive facts are facts that can be summed up for some of the dimensions in the fact table, but not the others. ... Non-Additive:

What is a factless fact table?

Factless Fact Table: In the real world, it is possible to have a fact table that contains no measures or facts. These tables are called "Factless Fact tables". Eg: A fact table which has only product key and date key is a factless fact. There are no measures in this table.

What is a fact table?

A fact table is the one which consists of the measurements, metrics or facts of business process. These measurable facts are used to know the business value and to forecast the future business. The different types of facts are explained in detail below. Additive facts are facts that can be summed up through all of the dimensions in the fact table.

What is an additive fact?

Additive facts are facts that can be summed up through all of the dimensions in the fact table. A sales fact is a good example for additive fact. Semi-additive facts are facts that can be summed up for some of the dimensions in the fact table, but not the others.

2. Semi Addictive Fact

Measurements in a fact table that can be summed up across only a few dimensions keys Following table is used to record current balance and profit margin for each id at a particular instance of time (Day end)

4. Factless fact table

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What is a factless fact table?

Factless fact- In the real world, it is possible to have a fact table that contains no measures or facts. These tables are called “Factless Fact tables”. Example – A fact table which has only product key and date key is a factless fact. There are no measures in this table.

Why is a product sold an additive fact?

The product sold is called additive fact because it can be summed up though all of the dimension in the fact table. Non-additive- Non-additive facts are facts that cannot be added for any of the dimensions present in the fact table. Example- Consider below fact table of a store:

What is data warehousing facts?

In data warehousing, facts and dimensions are standard terms. They inform us about things like the number of resources used for a particular task. They both store the exact measure of resources and details about the resource and task.

What is a fact table?

In a dimensional model, a fact table is a primary table. It contains facts, measurements, and metrics of a business process. It also acts as a foreign key to dimensional tables. The data stored in a fact table is often numerical. You can find a fact table at the center of a snowflake schema or star schema.

What is dimension in web design?

A website dimension consists of the website’s name and URL attributes. They describe different objects ...

What is dimension table?

Dimension tables often take the form of descriptive characteristics of facts and are helped by their attributes. Dimensions sometimes contain one or more hierarchical relationships.

What is junk dimension?

Junk dimensions form a collection of random transactional codes, text attributes, or flags. They often don’t logically belong to any specific dimension. Most often, the values of these attributes fall under simple (yes/no (or) true/false) indicators.

Why do we use degenerate dimensions?

As it’s derived from a fact table, it doesn’t have its own dimension. We use degenerate dimensions to collect snapshots of a fact table.

Where do product IDs come from?

For example, product IDs come from a product dimension table. However, as the invoice number is a standalone attribute with no attributes associated with it, the invoice number can be critical to keeping track of product quantities. Dimension-to-dimension table joins can reference other dimensions.