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
Data Warehouse Model
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 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 – 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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