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 gather,
provide access to, and analyze data and
information to support decision-making efforts
Sun Tzu in The Art of War
• To succeed in war, one should have full knowledge
of one’s own strengths and weaknesses
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: Data Rich, Information Poor
• 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 strategic asset for a business, and if the
asset is not used, the business is wasting resources.
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
– Predict sales and distribution schedules
– Determine correct inventory levels
– Forecast levels of bad loans and fraudulent credit card use
– Forecast credit card spending by new customers
– Predict machinery failures
– Determine key factors that control optimization of
manufacturing capacity
– Predict 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.
• Classify the most important elements that affect medical
coverage.
• Track crime patterns, locations and criminal behavior
• Forecast the cost of moving military equipment
• Testing 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
• Develop insights on symptoms and causes that result in
illness and how to provide proper treatments.
Having BI promotes understanding: Asking WHY?
• Where has the business been? (historical perspective)
• Where is the business now? (modify or encourage to continue)
• Where will the business be in the future? (predict future
direction)
DATA MINING
•
The center of any business intelligence effort is
data mining.
•
Data mining: the use of advanced statistical
techniques to analyze large amounts of data in
order to find patterns, relationships and infer rules
that might be used to predict future behavior.
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Uses query tools, multidimensional analysis,
intelligent agents and various statistical tools
Algorithms are applied to data sets to uncover
inherent trends and patterns in the data.
Goals of Data Mining
• Classification
• Trying to assign records to one of a predetermined set of classes.
• Estimation
• Determine values for an unknown continuous variable or estimate
future values.
• Affinity grouping
• Determine which things go together.
• Clustering
• Segment a diverse/differing population of records into groupings
with common characteristics
– Segmentation without having predetermined groups where the software
determines the groupings.
Most common forms of Data Mining
• Cluster analysis
• Association detection
• Statistical analysis
Cluster Analysis
•
Cluster analysis –
a technique used to
understand the
characteristics of a
group.
–
•
Classification uses a
predetermined grouping
while clustering looks at groupings determined by the
software.
CRM systems depend on cluster analysis to segment
customer information and identify behavioral traits
–
Segment by zip code, best customers or one-time customer.
Association Detection
•
Association detection – reveals the degree to
which variables are related and the nature
and frequency of these relationships in the
information
– Market basket analysis: trying to understand
which products are commonly purchased
together.
– Applications include :
•
•
cross-selling products and services
shelf-product placement.
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:
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Information correlations
Distributions, calculations, and variance analysis
Forecasting (most common form of statistical analysis)
Time series analysis
Prediction
Various what-if analysis
• The business intelligence tool used by most
organizations is Microsoft Excel and its data analysis
functionality, especially pivot tables.
• 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 relationships in the
data