refers to all of the applications and technologies used to gather, provide access to, and analyze data and information to support decision-making efforts. Putting together all of the pieces of the puzzle. ID: 689943
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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
Putting together all of the pieces of the puzzle
Chapter 5: Business IntelligenceSlide3
Business Intelligence vs Business Analytics
Business IntelligenceQuerying, reporting, online analytical processing, business analyticsBusiness AnalyticsA subset of BI based upon statistics, prediction and organization.
What happened? How many? How often?
Where the problem is What actions are needed
Why is this happening?
What will happen if these trends continue?
What will happen next?
What is the best (or worst) that can happen?Slide4
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.Slide5
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.), businesses are facing a digital explosion.
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.Slide6
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.Slide7
To improve the quality of business decisions, business intelligence tools and systems are used to make better, more informed decisions
Predict sales and distribution schedulesDetermine correct inventory levelsForecast levels of bad loans and fraudulent credit card useForecast credit card spending by new customersPredict 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 violationsSlide8
Forecast claim amounts and medical coverage costs.
Classify the most important elements that affect medical coverage.Track crime patterns, locations and criminal behaviorForecast the cost of moving military equipmentTesting strategies for potential military engagementsCapture 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.Slide9
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)Slide10
The center of any business intelligence effort is data mining.BI tells you what happened.Data mining tells you why it happened.
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.
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.Slide11
Data Mining Operations
Predict trends and behaviorsIdentify unknown patternsDetermine how things fit togetherWhat goes with what?Identify patternsAttempting to understand characteristicsSlide12
Goals of Data Mining
ClassificationTrying to assign records to one of a predetermined set of classes.
Determine values for an unknown continuous variable or estimate future values.
Determine which things go together.
Segment a diverse/differing population of records into groupings with common characteristics
Segmentation without having predetermined groups where the software determines the groupings.Slide13
Most common forms of Data Mining
Cluster analysisAssociation detectionStatistical analysisSlide14
Cluster analysis – a technique used to
characteristics of a
Classification uses a
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.Slide15
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
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 issueVarious types of statistical analysis that might be performed include:
Distributions, calculations, and variance analysis
Forecasting (most common form of statistical analysis)
Time series analysis
Various what-if analysisSlide17
The business intelligence tool used by most organizations is Microsoft Excel and its data analysis functionality, especially pivot tables.
By adding a Report Filter 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. Report Filters represent the depth layer
Slicers also let you do this
(multiple values for a given field)
Pivot Tables can help you see relationships in the dataSlide18Slide19Slide20
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