BUSINESS
INTELLIGENCE
Business intelligence
(BI) is a term used to describe a comprehensive, cohesive, and
integrated set of tools and processes used to capture, collect,
integrate, store, and analyze data with the purpose of generating
and presenting information used to support business decision
making.
PURPOSE
- BI is a framework
that allows a business to transform data into information,
information into knowledge, and knowledge into wisdom.
- Implementing BI in an
organization involves capturing not only business data (internal
and external) but also the metadata, or knowledge about the
data.
- BI provides a
well-orchestrated framework for the management of data that works
across all levels of the organization.
BI involves the
following general steps:
- Collecting and
storing operational data.
- Aggregating the
operational data into decision support data.
- Analyzing decision
support data to generate information.
- Presenting such
information to the end user to support business decisions.
- Making business
decisions, which in turn generate more data that is collected,
stored, etc. (restarting the process).
- Monitoring results to
evaluate outcomes of the business decisions (providing more data to
be collected, stored, etc.).
Business Intelligence Architecture:
- BI covers a range of
technologies and applications to manage the entire data life cycle
from acquisition to storage, transformation, integration, analysis,
monitoring, presentation, and archiving.
- BI functionality
ranges from simple data gathering and extraction to very complex
data analysis and presentation.
- The BI architecture
is composed of data, people, processes, technology, and the
management of such components.
The different
components of BI frame work are as follows.
ETL tools:
- Data extraction, transformation, and loading (ETL) tools
collect, filter, integrate, and aggregate operational data to be
saved into a data store optimized for decision support.
- For example, to determine the relative market share by selected
product lines, you require data on competitors' products.
- Such data can be located in external databases provided by
industry groups or by companies that market the data. As the name
implies, this component extracts the data, filters the extracted
data to select the relevant records, and packages the data in the
right format to be added to the data store component.
Data store:
- The data store is optimized for decision support and is
generally represented by a data warehouse or a data mart.
- The data store contains two main types of data: business data
and business model data.
- The business data are extracted from the operational database
and from external data sources. The business data is stored in
structures that are optimized for data analysis and query speed.
The external data sources provide data that cannot be found within
the company but that are relevant to the business, such as stock
prices, market indicators, marketing information (such as
demographics), and competitors’ data.
- Business models are generated by special algorithms that model
the business to identify and enhance the understanding of business
situations and problems.
Data query and analysis tools:
- This component
performs data retrieval, data analysis, and data-mining tasks using
the data in the data store.
- This component is
used by the data analyst to create the queries that access the
database. Depending on the implementation, the query tool accesses
either the operational database, or more commonly, the data
store.
- This tool advises the
user on which data to select and how to build a reliable business
data model.
- This component is
generally represented in the form of an OLAP tool.
Data presentation and visualization tools:
- This component is in
charge of presenting the data to the end user in a variety of
ways.
- This component is
used by the data analyst to organize and present the data.
- This tool helps the
end user select the most appropriate presentation format, such as
summary report, map, pie or bar graph, or mixed graphs.
- The query tool and
the presentation tool are the front end to the BI environment.
Decision
Support Data:
Although BI is used at
strategic and tactical managerial levels within organizations, its
effectiveness depends on the quality of data gathered at the
operational level.