What is Data Warehouse?
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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
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In the 1990’s executives became
less concerned with the day-to-day business operations and more concerned with
overall business functions
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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:
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Data warehouse – A logical
collection of information – gathered from many different operational databases
– that supports business analysis activities and decision-making takes
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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
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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.
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Data warehouse then send subsets
of the information to data mart.
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Data mart – contains a subset of
data warehouse information.
Multidimensional Analysis and
Data Mining
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Relational Database contains
information in a series of two-dimensional tables.
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In a data warehouse and data
mart, information is multidimensional, it contains layers of columns and rows
- Dimension – A particular attribute of information
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Cube – common term for the
representation of multidimensional information
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Once a cube of information is
created, users can begin to slice and dice the cube to drill down into the
information.
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Users can analyze information in
a number of different ways and with number of different dimensions.
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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
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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
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An organization must maintain
high-quality data in the data warehouse
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Information cleansing or
scrubbing – A process that weeds out and fixes or discards inconsistent,
incorrect or incomplete information
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Occurs during ETL process and
second on the information once if is in the data warehouse
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Contract information in an
operational system
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Standardizing Customer name
from Operational Systems
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Information cleansing activities
- Missing Records or Attributes
- Redundant Records
- Missing Keys or Other Required Data
- Erroneous Relationships or References
- Inaccurate Data
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Accurate and complete information
Business Intelligence
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Business Intelligence – refers to
applications and technologies that are used to gather, provides access, analyze
data and information to support decision making efforts
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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
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Eg; Excel, Access
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