Data Mining is used for the estimation of future. For example, if we take a company/business organization, by using the concept of Data Mining, we can predict the future of business in terms of Revenue (or) Employees (or) Customers (or) Orders etc.Traditional approaches use simple algorithms for estimating the future. However, it does not give accurate results when compared to Data Mining.
Star schema: A single fact table with N number of DimensionSnowflake schema: Any dimensions with extended dimensions are known as snowflake schema.
star schema: in this we have the centrally located fact tables surrounded by the number of dimensional tables where as in snow flake schema a denormalized dimensional table is subdivided into child dimensional tables
Junk dimension: Grouping of Random flags and text attributes in a dimension and moving them to a separate sub dimension. Degenerate Dimension: Keeping the control information on Fact table ex: Consider a Dimension table with fields like order number and order line number and have 1:1 relationship with Fact table, In this case this dimension is removed and the order information will be directly stored in a Fact table in order eliminate unnecessary joins while retrieving order information.
Gathering business requirements>>Identifying Sources>>Identifying Facts>>Defining Dimensions>>Define Attributes>>Redefine Dimensions / Attributes>>Organize Attribute Hierarchy>>Define Relationship>>Assign Unique Identifiers
Types of data warehousing are:
1. Enterprise Data warehousing
2. ODS (Operational Data Store)
3. Data Mart
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