CHAPTER 8: WHAT IS DATA WAREHOUSE

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 manly 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

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