MGT 300 CHAPTER 8 : Accessing Organizational Information – Data Warehouse

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

§  Issue 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 tasks

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

Relational Database contain 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.

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 find 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 find patterns and relationships in large volumes of information. Eg: retailers can 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  Occur during ETL process and second on the information once if is in the data warehouse

Contact information in an operational system

v  Standardizing Customer name from Operational Systems

v  Information cleansing activities

v  Accurate and complete information

v  Business intelligence – refers to applications and technologies that are used to gather, provide access, analyze data, and information to support decision making effort.

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