CHAPTER 8 : ACCESSING ORGANIZATIONAL INFORMATION - DATA WAREHOUSE

HISTORY OF DATA WAREHOUSE

• 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, because :

         *Operational information is mainly current - does not include the history for better decision
           making.
         *Issue of quality information
         *Without information history, it is difficult to tell how and why things change over time.

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.
• The primary purpose of a data warehouse is to combined information throughout an organization into a single repository for decision-making purposes - data warehouse support only analytical processing.

DATA WAREHOUSE MODEL

•  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.
• Data warehouse then send subsets of the information to data mart.
• Data mart - contains a subset of data warehouse information 

MULTIDIMENSIONAL ANALYSIS AND DATA MINING

•  Relational Database contain information in a series of two-dimensional tables.

 

• In a data warehouse and data mart, information is multidimensional, it contains layer of columns and rows

             *Dimension - a particular attribute of information

• Cube - common term for the representation of multidimensional information.

•  Once a cube of information is created, users can begin to slice and dice the cube to drill down into the information.
• Users can analyze information in a number of different ways and with number of different dimensions.
• Data mining -  the process of analyzing data to extract information not offered by the raw data alone. Also known as "knowledge discovery'' - computer-assisted tools and techniques for sifting through and analyzing vast data stores in order to find trends, patterns and correlations that can guide decision making and increase understanding.
• 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 informations. Eg : retailers can use knowledge of these
                                                 patterns to improve the placement of the items in the layout of a mail-
                                                 order catalog page or Web page.


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.
• Occur during ETL process and second on the information once if is in the data warehouse.

 

BUSINESS INTELLIGENCE

• Business intelligence -  refers to applications and technologies that are used to gather, provide access, analyze data and information to support decision making effort.
• These systems will illustrate business intelligence in the areas of customer profiling, customer support, market research, market segmentation, product profitability, statistical analysis, and inventory and distribution analysis to name a few.
• Example : Excel, Access