Chapter 1 Business Driven Technology
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Transcript Chapter 1 Business Driven Technology
Business Intelligence
Putting together all of the pieces of the puzzle
Business Plug-In B18 pages 466-482
Business intelligence (BI) refers to all of the
applications and technologies used to
,
provide access to, and
information to
efforts
Sun Tzu in The Art of War
• To succeed in war, one should have full
of one’s own
and
and
full knowledge of the enemy’s strengths and
weaknesses.
• Lack of either one might result in defeat.
Many businesses today say “how can I understand
my competitor when I can’t even understand myself.
That is what we are trying to solve using
business intelligence.
The Problem:
• With all of the data being captured and generated
by SCM, CRM and ERP systems, as well as the other
digital data being created and transmitted (spreadsheets,
fields in database files, word processing documents, video clips, email and text
messages, voice mail, etc.)
explosion.
, businesses are facing a digital
• The amount of data generated is doubling every
year
– Some believe it will soon double monthly
• Data is a
for a business, and if the asset
is not used, the business is
An Ideal Business Scenario
An account manager, on her way to a client visit, looks up past
proposals, as well as the client’s ordering, payment, delivery,
support and marketing history. At a glance, she can tell that
the client’s ordering volumes have dropped lately.
A few queries later, she understands that the client had support
issues with a given product. She calls her support
department and learns that the defective product will be
replaced within 24 hours.
In addition, the marketing records show that the client recently
attended a user conference and expressed interest in a new
product line.
With this information, she is prepared for a constructive sales
call. She understands all aspects of a client’s relationship with
her firm, understands the client’s issues and can confidently
address new sales opportunities.
• To improve the quality of business decisions,
business intelligence tools and systems are used to
make better, more informed decisions
–P
and distribution schedules
– Determine correct inventory levels
–F
levels of bad loans and fraudulent credit card use
– Forecast credit card spending by new customers
– Predict machinery failures
–D
key factors that control optimization of
manufacturing capacity
–P
when bond prices might change
– Determine when to buy or sell stocks
– Predict hard drive failures
– Predict potential security violations
• Forecast claim amounts and medical coverage costs.
• C
the most important elements that affect medical
coverage.
• T
crime patterns, locations and criminal behavior
• Forecast the cost of moving military equipment
• T
strategies for potential military engagements
• Capture data on where customers are flying and the
ultimate destination of passengers who change airlines in
hub cities: is there a new route that should be added?
• Predict what type of show is best to air during prime time
and how to maximize returns by interjecting commercials
• D
on symptoms and causes that result
in illness and how to provide proper treatments.
Having BI promotes understanding: Asking WHY?
• W
• W
? (historical perspective)
? (modify or encourage to continue)
• Where
(predict future direction)
DATA MINING
•
The center of any business intelligence effort is
•
Data mining: the use of
to
large amounts of
in
order to
that might be used to predict future behavior.
•
•
Uses query tools, multidimensional analysis,
intelligent agents and various statistical tools
Algorithms are applied to data sets to
inherent
and
in the data.
Goals of Data Mining
• C
• Trying to assign records to one of a predetermined set of classes.
• E
• Determine values for an unknown continuous variable or estimate
future values.
• Affinity grouping
• D
• Clustering
• Segment a diverse/differing population of records into groupings
with common characteristics
Most common forms of Data Mining
• Cluster analysis
• Association detection
• Statistical analysis
Cluster Analysis
•
Cluster analysis –
a technique used to
into mutually
exclusive
such
that the members of
each group are as close
together as possible to one another and the different
groups are as far apart as possible
•
CRM systems depend on cluster analysis to segment
customer information and identify behavioral traits
–
Segment by
, best customers or one-time customer.
Association Detection
•
Association detection – reveals the degree to
and the nature
and frequency of these relationships in the
information
– Market basket analysis: trying to understand
– Applications include :
•
•
C
s
products and services
Statistical Analysis
•
A wide range of statistical tools that can be used to build
various statistical models, examine the model’s
assumptions and validity, as well as compare and contrast
the various models to determine the best one to use for a
particular business issue
•
Various types of statistical analysis that might be performed
include:
–
–
–
–
–
–
Information correlations
Distributions, calculations, and variance analysis
F
(most common form of statistical analysis)
T
Prediction
Various
• The business intelligence tool used by most
organizations is
and its data
analysis functionality, especially
• By adding a Page Field to a Pivot Table, you can add
another dimension of information: 3-D (rows and
columns and layers).
– Creating a 3-dimensional Pivot Table in Excel is a means
of conceptually building a data warehouse. Page fields
represent the depth layer
• Pivot Tables can help you see