CHAPTER 8

Chapter 8 – Accessing Organizational Information – Data Warehouse

WHAT IS DATA WAREHOUSE?

v   Defined in many different ways, but not rigorously

         -  A decision support database that is maintained separately from the organization’s operational database.

         -  A consistent database source that bring together information from multiple sources for decision support queries.

         -  Support information processing by providing a solid platform of consolidated, historical data for analysis.

HISTORY OF DATA WAREHOUSING

v   In the 1990’s executives became less concerned with the day-to-day business operations and more concerned with overall business functions

v   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

       -   Issues of quality information

       -   Without information history, it is difficult to tell how and why things change over time

DATA WAREHOUSE FUNDAMENTALS

v   Data warehouse – A logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making takes

v   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

v   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.

v   Data warehouse then send subsets of the information to data mart.

v   Data mart – contains a subset of data warehouse information.

 

MULTIDIMENSIONAL ANALYSIS AND DATA MINING

v   Relational Database contains information in a series of two-dimensional tables.

v   In a data warehouse and data mart, information is multidimensional, it contains layers of
   columns and rows

        -  Dimension – A particular attribute of information

 

v   Cube – common term for the representation of multidimensional information

 

v   Once a cube of information is created, users can begin to slice and dice the cube to drill down
    into the information.

v   Users can analyze information in a number of different ways and with number of different dimensions.

v   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 finds trends, patterns and correlations that can guide decision making and increase understanding

v   To perform data mining users need data-mining tools

          -  Data-mining tool – uses a variety of techniques to finds patterns and relationships in large volumes of information. Eg: retailers and use knowledge of these patterns to improve the placement of items in the layout of a mail-order catalog page or Web page.

INFORMATION CLEANSING OR SCRUBBING

v   An organization must maintain high-quality data in the data warehouse

v   Information cleansing or scrubbing – A process that weeds out and fixes or discards inconsistent, incorrect or incomplete information

v   Occurs during ETL process and second on the information once if is in the data warehouse

v   Contract information in an operational system

v   Standardizing Customer  name from Operational Systems

v   Information cleansing activities

-   Missing Records or Attributes

-   Redundant Records

-   Missing Keys or Other Required Data

-   Erroneous Relationships or References

-   Inaccurate Data

v   Accurate and complete information

 

BUSINESS INTELLIGENCE

v   Business Intelligence – refers to applications and technologies that are used to gather, provides access, analyze data and information to support decision making efforts

v   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

v   Eg; Excel, Access