文档介绍：Data Warehousing and OLAP Technology
What is a data warehouse?
A multi-dimensional data model
Data warehouse architecture
Data warehouse implementation
Further development of data cube technology
From data warehousing to data mining
What is Data Warehouse?
Defined in many different ways, but not rigorously.
A decision support database that is maintained separately from anization’s operational database
Support information processing by providing a solid platform of consolidated, historical data for analysis.
“A data warehouse is a subject-oriented, integrated, time-variant, and nonvolatile collection of data in support of management’s decision-making process.”—W. H. Inmon
Data warehousing:
The process of constructing and using data warehouses
Data Warehouse—Subject-Oriented
Organized around major subjects, such as customer, product, sales.
Focusing on the modeling and analysis of data for decision makers, not on daily operations or transaction processing.
Provide a simple and concise view around particular subject issues by excluding data that are not useful in the decision support process.
Data Warehouse—Integrated
Constructed by integrating multiple, heterogeneous data sources
Relational databases, flat files, on-line transaction records
Data cleaning and data integration techniques are applied.
Ensure consistency in naming conventions, encoding structures, attribute measures, etc. among different data sources
., Hotel price: currency, tax, breakfast covered, etc.
When data is moved to the warehouse, it is converted.
Data Warehouse—Time Variant
The time horizon for the data warehouse is significantly longer than that of operational systems.
Operational database: current value data.
Data warehouse data: provide information from a historical perspective (., past 5-10 years)
Every key structure in the data warehouse
Contains an element of time, explicitly or implicitly
But the key of operational data may or may not contain “time element”.
Data Warehou