CHAPTER 8

Chapter 8 – Accessing Organizational Information – Data Warehouse

What is Data Warehouse?

:)  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

:)  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

-          Issues 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 takes

:)  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 info

Multidimensional Analysis and Data Mining

:)  Relational Database contains 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

:)  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 finds 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 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

:)  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

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

:)  Contract information in an operational system

:)  Standardizing Customer  name from Operational Systems

:)  Information cleansing activities

-          Missing Records or Attributes

-          Redundant Records

-          Missing Keys or Other Required Data

-          Erroneous Relationships or References

-          Inaccurate Data

Business Intelligence

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

:)  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

:)  Eg; Excel, Access