Data warehouse kimball model
How do you model data in a data warehouse?
Data warehouse modeling is the process of designing and organizing your data models within your data warehouse platform.
The design and organization process consists of setting up the appropriate databases and schemas so that the data can be transformed and then stored in a way that makes sense to the end user..
What data warehouse approaches was given by Ralph Kimball?
As proposed by Ralph Kimball, the bottom-up method calls for the creation of many data marts to satisfy the analytical needs of departments, followed by virtual integration of these data marts for consistency through an information bus..
What is Kimball model approach?
Kimball's approach.
First introduced by Ralph Kimball, Kimball's approach focuses on a bottom-up procedure: Start by understanding and documenting the most critical business processes, business needs, and business questions being asked.
Document all data sources available throughout the enterprise..
- Kimball happens to be process-oriented since the focus is on business processes.
Kimball prefers the denormalized data model, and as such, we find redundant data model present in the Kimball architecture. - Physical Data Model
It is created by using the database language and queries.
The physical data model provides database column keys, constraints, and RDBMS features.
We create various schemas, abstraction of schemas, and different mapping types in these data models. - Slowly changing dimension type 3 changes add a new attribute in the dimension to preserve the old attribute value; the new value overwrites the main attribute as in a type 1 change.
This kind of type 3 change is sometimes called an alternate reality.
In The Data Warehouse Toolkit, Ralph Kimball describes how keeping track of inventory movements is a common business activity for many types of businesses. He
What is Kimball approach to data warehouse lifecycle?
To integrate data, Kimball approach to Data Warehouse lifecycle suggests the idea of conformed data dimensions
It exists as a basic dimension table shared across different fact tables (such as customer and product) within a data warehouse or as the same dimension tables in various Kimball data marts
What is Kimball dimensional modeling?
Kimball dimensional modeling allows users to construct several star schemas to fulfill various reporting needs
The advantage of star schema is that small dimensional-table queries run instantaneously
To integrate data, Kimball approach to Data Warehouse lifecycle suggests the idea of conformed data dimensions
Ralph Kimball initiated the Kimball data warehouse approach, where the Kimball data model follows a bottom-up approach to data warehouse (DW) architecture design in which data marts are formed first based on the business requirements.
In business intelligence, data classification has close ties to data clustering, but where data clustering is descriptive, data classification is predictive.
In essence data classification consists of using variables with known values to predict the unknown or future values of other variables.
It can be used in e.g. direct marketing, insurance fraud detection or medical diagnosis.
The functional database model is used to support analytics applications such as financial planning and performance management.
The functional database model, or the functional model for short, is different from but complementary to the relational model.
The functional model is also distinct from other similarly named concepts, including the DAPLEX functional database model and functional language databases.
