CHAPTER
EIGHT – ACCESSING ORGANIZATIONAL INFORMATION-DATA WAREHOUSE
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 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
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
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