What is Data Warehouse?
Ø Defined in many different ways, but not rigorously
- A decision support database that is maintained separately from the organization’s operational database.
- A consistent database source that bring together information from multiple sources for decision support queries.
- Support information processing by providing a solid platform of consolidated, historical data for analysis.
History of Data Warehousing
Ø In the 1990’s executives became less concerned with the day-to-day business operations and more concerned with overall business functions
Ø 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
- Issues of quality information
- Without information history, it is difficult to tell how and why things change over time
Data warehouse fundamentals
Ø Data warehouse – A logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making takes
Ø 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
Ø 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.
Ø Data warehouse then send subsets of the information to data mart.
Ø Data mart – contains a subset of data warehouse information.
Multidimensional Analysis and Data Mining
Ø Relational Database contains information in a series of two-dimensional tables.
Ø In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows
- Dimension – A particular attribute of information
Ø Cube – common term for the representation of multidimensional information
Ø Once a cube of information is created, users can begin to slice and dice the cube to drill down into the information.
Ø Users can analyze information in a number of different ways and with number of different dimensions.
Ø 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 finds trends, patterns and correlations that can guide decision making and increase understanding
Ø To perform data mining users need data-mining tools
- Data-mining tool – uses a variety of techniques to finds patterns and relationships in large volumes of information. Eg: retailers and 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
Ø An organization must maintain high-quality data in the data warehouse
Ø Information cleansing or scrubbing – A process that weeds out and fixes or discards inconsistent, incorrect or incomplete information
Ø Occurs during ETL process and second on the information once if is in the data warehouse
Ø Contract information in an operational system
Ø Standardizing Customer name from Operational Systems
Ø Information cleansing activities
- Missing Records or Attributes
- Redundant Records
- Missing Keys or Other Required Data
- Erroneous Relationships or References
- Inaccurate Data
Ø Accurate and complete information
Business Intelligence
Ø Business Intelligence – refers to applications and technologies that are used to gather, provides access, analyze data and information to support decision making efforts
Ø 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
Ø Eg; Excel, Access
Question?
1. Describe the roles and purposes of data warehouse and data marts in an organization
2. Compare the multidimensional nature of data warehouses (and data marts) with the two-dimensional nature of databases
3. Identify the information of ensuring the cleanliness of information throughout an organization
4. Explain the relationship between business intelligence and a data warehouse
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