1. Data Warehouse and OLAP
Data Mining: Concepts and Techniques
by J. Han and M. Kamber
11/19/2018
CSE591: Data Mining by H. Liu

2. What is a data warehouse?
A repository of information collected from multiple sources, stored under a unified schema at a single site
Characteristics:
Subject-oriented
Integrated
Time-variant
Nonvolatile
A semantically consistent data store for decision support at enterprise level
11/19/2018
CSE591: Data Mining by H. Liu

3. Data warehousing and a multidimensional data model
DWing - the process of constructing and using DW.
OLTP and OLAP: user & system orientation, data contents, database design, view, access patterns (Table 2.1)
A DW is usually modeled by a multidimensional database structure - a data cube
An example of a data cube of Student Information
dimensions: nationality, level, status, …
11/19/2018
CSE591: Data Mining by H. Liu

4. Schemas for multidimensional databases
OLTP and OLAP on the same databases(?)
achieving high performance of both systems
Dimensions are the perspectives or entities
Facts are numeric measures
Dimension table and fact table
DW schemas
Star
Snowflakes
Fact constellations
11/19/2018
CSE591: Data Mining by H. Liu

5. Examples for defining schemas
define cube, define dimension …as…in
Star
Fig. 2.4
Example 2.4
Snowflake
Fig. 2.5
Example 2.5
Fact constellation
Fig. 2.6
Example 2.6
11/19/2018
CSE591: Data Mining by H. Liu

6. CSE591: Data Mining by H. Liu
OLAP operations
Concept hierarchy
one for each dimension
Operations (Fig. 2.10)
Dice
Slice
Pivot
Roll-up
Drill-down
11/19/2018
CSE591: Data Mining by H. Liu

7. Data Warehouse Architecture
A 3-tier data warehouse architecture
Front-end tools
OLAP server
Data warehouse server
Three models:
Enterprise warehouse
Data mart
Virtual warehouse
11/19/2018
CSE591: Data Mining by H. Liu

8. CSE591: Data Mining by H. Liu
Metadata Repository
When used in DW, metadata are the data that define warehouse objects:
a directory to help the decision support system analyst locate the contents of the DW
a guide to the mapping of data from the source to the DW
a guide to the algorithms used for summarization
A metadata repository contains
the DW structure, operational metadata, algorithms used, mapping, data related to system performance, business metadata
11/19/2018
CSE591: Data Mining by H. Liu

9. CSE591: Data Mining by H. Liu
From DW to DM
DW back-end tools and utilites
data extraction, cleaning, transformation, load, refresh
The uses of DW
generate reports and answer predefined queries
analyze summarized and detailed data
performing multidimensional analysis
knowledge discovery and strategic decision making using data mining
Information, analytical processing and DM
11/19/2018
CSE591: Data Mining by H. Liu