CHAPTER 8 : ACCESSING ORGANIZATIONAL INFORMATION-DATA WAREHOUSE

History of Data Warehouse

• 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 models

• 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 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 analyse information in a number of different ways and with number of different dimensions

Multidimensional Analysis and Data Mining

• Data mining – the process of analysing 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 analysing 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 information. 
• Examples: retailers can use knowledge of these patterns to improve the placement of items in the layout of a 

           mail-order catalogue 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
• Contact information in an operational system

• Standardizing Customer name from Operational Systems

• Information cleansing activities

• Accurate and complete information

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

• Eg: Excel, Access