MGT300-CHAPTER 8
ACCESSING ORGANIZATIONAL INFORMATION - DATA WAREHOUSE
History of Data Warehousing
- In the 1990's executives became less concerned with the day-to-day business operatios and with more concerned with overall business functions.
- The data warehouse provided the ability to support decision making without disrupting the day-to-day operations because :
- Issue of quality information
- Without information history, it is difficult to say how and why things change over time
Data Warehouse Fundamentals
- Data Warehouse - a logical collection of information - gathered from many different operational databases - that support business analysis activities and decision-making tasks
- The primary purpose of 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 extract information from internal and external databases, transform the information using a common set of enterprise definitions, and loads the information into a data warehouse
- Data warehouse then send subsets of information to data mart
- Data mart - contains a subsets of data warehouse information
- Once a cube of information is created, users can begin to slice and dice the cube to drill down 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" - compute assisted tools and techniques for sitting through and analyzing 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
Business Intelligence
- Refer to application 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 customers profiling, customers support, market research, market segmentation, product profitability,satistical analysis, and inventory and distribution analysis to name a few
- Eg, excel,access
Information Cleansing and Scrubbing
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