Information Technology In Business: CHAPTER 8

ACCESSING ORGANIZATIONAL INFORMATION - DATA WAREHOUSE

In this chapter, we learned about :

Descibe the roles and purposes of data warehouses and data marts in an organization
Compare the multidimensional nature of data warehouses (and data marts), with the two-dimensional nature of databases
Identify the importance of ensuring the cleanliness of information throughout an organization
Explain the relationship between business intelligence and a data warehouse

HISTORY OF DATA WAREHOUSING

Data warehouses extend the transformation of data into information
In the 1990's executives became less concerned with the day-to-day business operations and more concerned with overall business functions
The data warehouse provided the ability to support decision making without disrupting the day-to-day operations

DATA WAREHOUSES FUNDAMENTALS

Data warehouse - A logical collection of information - gathered from many different operational databases - that supports business analysis activities and decision-making tasks
The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision-making purposes
Extraction, transformation, and loading (ETL) - A process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse
The ETL process gathers data from the internal and external databases and passes it to the data warehouse
The ETL process also gathers data from the data warehouse and passes it to the data marts
Data mart - Contains a subset of data warehouse information

MULTIDIMENSIONAL ANALYSIS AND DATA MINING

Databases contain information in a series of two-dimensional tables
In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows

- Dimension - A particular attribute of information

Each layer in a data warehouse or data mart represents information according to an additional dimension
Dimensions could include such things as :

- Products

- Promotions

- Stores

- Category

- Region

- Stock price

- Date

- Time

- Weather

Cube - Common term for the representation of multidimensional information

- Users can slice and dice the cube to drill down into the information

- Cube A represents store information (the layers), product information (the rows), and promotion information (the columns)

- Cube B represents a slice of information displaying promotion II for products at all stores

- Cube C represents a slice of information displaying promotion III for product B at store 2

Data mining - The process of analyzing data to extract information not offered by the raw data alone
To perform data mining users need data mining tools

- Data mining tool - Uses a variety of techniques to find patterns and relationships in large volumes of information and infers ruler that predict future behavior and guide decision making

Data mining can begin at a summary information level (course granularity) and progress through increasing levels of detail (drilling down), or the reverse (drilling up)
Data-mining tools include query tools, reporting tools, multidimensional analysis tools, statistical tools, and intelligent agents

INFORMATION CLEANSING OR SCRUBBING

An organization must maintain high-quality data in the data warehouse
Information cleansing or scrubbing - A process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information
Contact information in an operational system