Data warehousing involves integrating data from disparate sources into a central repository for business analytics and reporting. The data warehouse stores historical data separately from daily operations. Common warehouse schemas include star and snowflake, arranging dimensions and facts for simpler queries. Online analytical processing (OLAP) cubes represent these schemas to answer multi-dimensional queries swiftly with measures and dimensions. Reports are then generated from the analyzed data.

1. Data Warehousing
Matouš Havlena
matous@havlena.net
Big Data Analytics
UTC

2. Why data warehousing?
Data Information Decision

3. Data warehouse
Data warehouse is a database used for reporting and data
analysis. It is a central repository of data which is created by
integrating data from one or more disparate sources.
Data warehouse is a pool of historical data that doesn’t
participate in the daily operations of the organization.
Instead, this data is purposefully used for business analytics.

5. Warehouse schemas - star
● Data in DW is arranged into hierarchical
groups called dimensions and into facts
● The simplest style of DW schema.
● Consists of one or more fact tables
referencing any number of dimension tables.
● Special case of the snowflake schema, and is more effective for
handling simpler queries.

6. Warehouse schemas - snowflake
● Multiple dimensions
● Star and snowflake schemas are most commonly found in
dimensional data warehouses and data marts where speed of data
retrieval is more important than the efficiency of data manipulations
● Don’t follow normal forms - speed tradeoff

7. OLAP cubes
● Online Analytical Processing
● An approach to answering multi-dimensional
queries swiftly
● Represents star schema or snowflake schema in a relational data
warehouse
● Each cell of the cube holds a number that represents some measure
of the business, such as sales, profits, expenses, budget and
forecast
● Measures are derived from the records in the fact table and
dimensions are derived from the dimension tables
● Operations: Slice and Dice, Drill-up and Drill-down, Roll-up

9. Reports

10. Questions?
Thank you!
Matouš Havlena
matous@havlena.net