Chapter 8 : Accessing Organization Information- Data Warehouse

                  HISTORY OF DATA WAREHOUSE

• 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 WAREHOUSE FUNDAMENTALS

Data warehouse – a logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision making  tasks

Extraction, transformation, and loading (ETL) – a process that extracts information  internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse

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
•        Cube - common term for the representation of multidimensional information. 
•       Data mining – the process of analyzing data to extract information not offered by the raw data alone

      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

INFORMATION CLEANSING ACTIVITIES

BUSINESS INTELLIGENCE 

• Business intelligence – information that people use to support their decision making efforts

• Principle BI enablers include:

              –Technology

               –People

                –Culture