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Business Intelligence Advancements Transform Corporate
Article:
Companies have long considered data collection and analysis to
be fundamental activities for long term strategic planning.
Before the rise of the Information Age, most decision making was
based on guess-work or trial-and-error practices. Businesses
seeking to achieve a sustainable advantage over their
competition quickly turned to information management systems for
detailed data analysis. These systems and methods have evolved
to what is now known by the broader term "business intelligence"
or "BI".
Business intelligence refers to in-depth analysis of company
data for better decision-making. The technology and processes
that make this analysis possible take unwieldy collections of
information and translate them into organized,
readily-accessible, human-readable compilations of data. With an
effective BI tool, companies can easily track their own
operations, their customers' activity patterns, and industry
trends. These fact-based assessments help companies work toward
specific goals with confidence.
The business intelligence process can be broken down into the
following three stages:
4. Data 5. Information 6. Knowledge
Raw data is gathered and processed into information. The
information must be filtered and arranged into meaningful
patterns. The knowledge drawn from that data analysis helps to
form the business intelligence of a corporation.
Business intelligence needs vary across industries. The
functional area and particular processes under examination play
a large role in the type of data gathered and the range of
knowledge sought. Common functional areas include: Sales and
Marketing, Human Resources, Operations, and Finance.
Sales and marketing departments track products, customers,
demographics, promotions, sales force, order type, and other
related fields. Human resources groups often look to measure
employee, organizational, and departmental issues. Assembly
speed, warehouse stock, manufacturer and supplier cost, and
shift productivity are the domain of operations management.
Finance departments will closely watch data on topics such as
currency standards, account information, and industry trends.
In the field of business intelligence, staff organizational
levels also come into play. Those in lower organizational levels
are more likely to focus on measures of short-term, correctable
performance while more senior employees may measure high-level
trends instead of absolutes. Of course, both of these types of
measures are important to gauging a company's relative success.
Good business intelligence means balanced information. Too much
or too little data is not useful. Corporations can focus on the
most crucial improvements by setting reasonable limits on the
information gathered, coordinating the efforts around a
company-wide strategy, and employing business
intelligence systems.
Intelligence support systems can improve day-to-day business
decision-making. Once a company has decided to adopt a business
intelligence strategy, the first step in the process is to
decide on goals for the initiative. After a central goal has
been agreed upon, such as providing shareholders with a return
above the industry-average, it is important to assess where
overall decision making can be improved and to target the most
valuable areas.
To facilitate their efforts, businesses may choose from a
variety of intelligence support products on the market. Common
tools include: data warehouses, business performance management,
data mining or KDD (knowledge-discovery in databases), document
warehouses, text mining, data visualization, scorecarding, and
OLAP (Online Analytical Processing). These products work to sort
through raw data and contribute to informed decision making.
Some of these tools can produce compelling results when applied
in tandem. For example, data and document warehouses used in
tracking a store's inventory can be linked to show both company
data on past sales trends and external articles containing
consumer opinions, thus expanding the pool of information
available for decision-support and providing a more complete
understanding of the situation.
Software-oriented business intelligence is seen by some as the
next phase in the movement. Companies with limited Information
Technology (IT) resources or whose data is held in disparate
data sources can rely on software such as DecisionCentric® or
Decision Analyzer®. Both products are produced by Decision
Technology, Inc.. They enable users to analyze data, create
reports, and export files to other applications like Acrobat,
Word, and Excel. DecisionCentric®, in particular, is a powerful
business intelligence application for small to midsize
companies. At its heart is an EII engine optimized for small and
midsize organizations. This allows organizations to postpone
data warehouse implementations or extend the power and reach of
any existing data warehouse. Moreover, the software program
offers a free-form reporting tool that does the heavy lifting of
report design to make the end-user's job easier.
Business intelligence is prevalent in virtually every level of
corporate dealings, in every industry. Technological advances
require companies to make 'round-the-clock decisions at a
moment's notice. The companies that can develop winning
strategies in the face of increased competition and mountains of
data will triumph over their competitors.
Busines
s intelligence products guarantee companies the
confidence of knowing the current fact-based information they
need will always be right at their fingertips.
About Decision Technology, Inc. Decision Technology
business intelligence software is the ideal solution for
organizations with limited IT resources, and whose data are
confined in disparate databases or operational systems. Since
1985, Decision Technology has provided organizations with
intuitive, information retrieval software for decision support
applications. Its newest business intelligence software product,
DecisionCentric, provides Enterprise Information Integration
with query and reporting tools optimized for small and medium
size organizations. It enables users to integrate, publish and
analyze enterprise data across disparate data sources - without
expensive ETL technology.
This article is copyrighted by Decision Technology. It may not
be reproduced in whole or in part and may not be posted on other
websites, without the express written permission of the author
who may be contacted via email at
DTI@digitalbrandexpressions.com.
About the author:
R.L. Fielding has been a freelance writer for 10 years, offering
her expertise and skills to a variety of major organizations in
the education, pharmaceuticals and healthcare, financial
services, and manufacturing industries. She lives in New Jersey
with her dog and two cats and enjoys rock climbing and
ornamental gardening.
This article is copyrighted by Decision Technology. It may not
be reproduced in whole or in part and may not be posted on
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