8.1 Describe the roles and purposes of data warehouses and data marts in an organization
8.2 Compare the multidimensional nature of data warehouses (and data marts) with the two-dimensional nature of databases
8.3 Identify the importance of ensuring the cleanliness of information throughout an organization
8.4 Explain the relationship between business intelligence and a 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 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 – 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
- 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
- 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 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 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. 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
- 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
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