Business Intelligence Systems

Chapter 9

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“We Can Make the Bits Produce Any Report You

Want, But You’ve Got to Pay for It.”

• Need to monitor patient workout data.

• Spending too many hours each day looking at patient

workout data.

• Great use for exception reporting.

• Animation & new types of reporting creates innovative and

motivating reports.

• Eliminating silos enables everyone to gain more information

from PRIDE data.

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Study Questions

Q1: How do organizations use business intelligence (BI) systems?

Q2: What are the three primary activities in the BI process?

Q3: How do organizations use data warehouses and data marts to acquire data?

Q4: How do organizations use reporting applications?

Q5: How do organizations use data mining applications?

Q6: How do organizations use BigData applications?

Q7: What is the role of knowledge management systems?

Q8: What are the alternatives for publishing BI?

Q9: 2024?

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Q1: How Do Organizations Use Business Intelligence

(BI) Systems?

Components of Business

Intelligence System

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Example Uses of Business Intelligence

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What Are Typical Uses for BI?

• Identifying changes in purchasing patterns

– Important life events cause customers to change what they buy.

• BI for entertainment

– Netflix has data on watching, listening, and rental habits, however,

determines what people actually want, not what they say.

• Predictive policing

– Analyze data on past crimes, including location, date, time, day of

week, type of crime, and related data, to predict where crimes are

likely to occur.

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Q2: What Are the Three Primary Activities in the BI

Process?

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Using Business Intelligence to Find Candidate Parts at

AllRoad

• Identified criteria for parts customers might want to print

themselves.

– Provided by vendors who already agree to make part

design files available for sale.

– Purchased by larger customers.

– Frequently ordered parts.

– Ordered in small quantities.

– Simple in design.

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Acquire Data: Extracted Order Data

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Extracted Part Data

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Analyze Data: Access Query

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Query Result

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Joining Order Extract and Filtered Parts Tables

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Sample Orders and Parts View Data

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Customer Summary

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Qualifying Parts Query Design

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Qualifying Parts Query Results Figure

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Publish Results: Sales History for Selected Parts

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Q3: How Do Organizations Use Data Warehouses and

Data Marts to Acquire Data?

Functions of a Data Warehouse

• Extract data from operational, internal and external

databases.

• Cleanse data.

• Organize, relate data warehouse.

• Catalog data using metadata.

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Components of a Data Warehouse

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Examples of Consumer Data That Can Be Purchased

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Possible Problems with Source Data

Curse of

dimensionality

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Data Warehouses Versus Data Marts

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Q4: How Do Organizations Use Reporting

Applications?

• Create meaningful information from disparate data sources.

• Deliver information to user on time.

• Basic operations:

1. Sorting

2. Filtering

3. Grouping

4. Calculating

5. Formatting

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How Does RFM Analysis Classify Customers?

• Recently

• Frequently

• Money

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RFM Analysis Classifies Customers

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Typical OLAP Report

OLAP Product Family by Store Type

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Example of Expanded Grocery Sales OLAP Report

Drill

down into

the data

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OLAP Product Family and Store Location by Store Type,

Showing Sales Data for Four Cities

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Q5: How Do Organizations Use Data Mining

Applications?

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Unsupervised Data Mining

• Analyst does not start with a priori hypothesis or model.

• Hypothesized model created based on analytical results to

explain patterns found.

• Example: Cluster analysis.

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Supervised Data Mining

• Uses a priori model to compute outcome of model

• Prediction, such as regression analysis

• Ex: CellPhoneWeekendMinutes

= (12 + (17.5*CustomerAge)+(23.7*NumberMonthsOfAccount)

= 12 + 17.5*21 + 23.7*6 = 521.7

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Market-Basket Analysis

• Market-basket analysis – a data-mining technique for determining sales patterns. – Statistical methods to identify sales patterns in large

volumes of data. – Products customers tend to buy together. – Probabilities of customer purchases. – Identify cross-selling opportunities.

Customers who bought fins also bought a mask.

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Market-Basket Example: Dive Shop

Transactions = 400

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Decision Trees

• Hierarchical arrangement of criteria to predict a classification

or value.

• Unsupervised data mining technique.

• Basic idea of a decision tree

– Select attributes most useful for classifying something

on some criteria to create “pure groups”.

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Credit Score Decision Tree

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Decision Rules for Accepting or Rejecting Offer to

Purchase Loans

If percent past due is less than 50 percent, then accept loan.

• If percent past due is greater than 50 percent and

• If CreditScore is greater than 572.6 and

• If CurrentLTV is less than .94, then accept loan.

• Otherwise, reject loan.

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Using MIS InClass Exercise 9: What Singularity Have

We Wrought?

Trends in the Computing Industry

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Q6: How Do Organizations Use BigData Applications?

• Huge volume – petabyte and larger.

• Rapid velocity – generated rapidly.

• Great variety

– Structured data, free-form text, log files, possibly

graphics, audio, and video.

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MapReduce Processing Summary

Google search

log broken into

pieces

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Google Trends on the Term Web 2.0

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Hadoop

• Open-source program supported by Apache Foundation2.

• Manages thousands of computers.

• Implements MapReduce

– Written in Java

• Amazon.com supports Hadoop as part of EC3 cloud offering.

• Query language entitled Pig.

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Q7: What Is the Role of Knowledge Management

Systems?

• Knowledge Management

– Creating value from intellectual capital and sharing that

knowledge with those who need that capital.

– Preserving organizational memory by capturing and

storing lessons learned and best practices of key

employees.

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Benefits of Knowledge Management

• Improve process quality.

• Increase team strength.

• Goal:

– Enable employees to use organization’s collective

knowledge.

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What Are Expert Systems?

Expert systems

Rule-based IF/THEN

Encode human knowledge

Process IF side of rules

Report values of all variables

Knowledge gathered from human experts

Expert systems shells

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Example of IF/THEN Rules

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Drawbacks of Expert Systems

1. Difficult and expensive to develop

– Labor intensive

– Ties up domain experts

2. Difficult to maintain

– Changes cause unpredictable outcomes

– Constantly need expensive changes

3. Don’t live up to expectations

– Can’t duplicate diagnostic abilities of humans

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What Are Content Management Systems (CMS)?

• Support management and delivery of documents, other expressions of

employee knowledge

• Challenges of Content Management

– Databases are huge

– Content dynamic

– Documents do not exist in isolation

– Contents are perishable

– In many languages

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What are CMS Application Alternatives?

• In-house custom

– Customer support department develops in-house database

applications to track customer problems

• Off-the-shelf – Horizontal market products (SharePoint)

– Vertical market applications

• Public search engine

– Google

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How Do Hyper-Social Organizations Manage

Knowledge?

• Hyper-social knowledge management

– Application of social media and related applications for

management and delivery of organizational knowledge

resources.

• Hyper-organization theory

– Framework for understanding this new direction in KM.

– Focus moves from knowledge and content per se to fostering

authentic relationships among creators and users of

knowledge.

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Hyper-Social KM

Alternative Media

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Q8: What Are the Alternatives for Publishing BI?

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Elements of a BI System

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Q9: 2024?

• World generating and storing exponentially more information.

• Information about customers, and data mining techniques going

to get better.

• Companies will know more about your purchasing habits and

psyche.

• Social singularity – Machines will build their own information

systems.

• Will machines possess and create information for themselves?

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Guide: Semantic Security

1. Unauthorized access to protected data and information

– Physical security

Passwords and permissions

Delivery system must be secure

2. Unintended release of protected information through reports and documents.

3. What, if anything, can be done to prevent what Megan did?

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Guide: Data Mining in the Real World

• Problems:

– Dirty data

– Missing values

– Lack of knowledge at start of project

– Over fitting

– Probabilistic

– Seasonality

– High risk – unknown outcome

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Active Review

Q1: How do organizations use business intelligence (BI) systems?

Q2: What are the three primary activities in the BI process?

Q3: How do organizations use data warehouses and data marts to acquire data?

Q4: How do organizations use reporting applications?

Q5: How do organizations use data mining applications?

Q6: How do organizations use BigData applications?

Q7: What is the role of knowledge management systems?

Q8: What are the alternatives for publishing BI?

Q9: 2024?

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Case Study 9: Hadoop the Cookie Cutter

• Third-party cookie created by a site other than one you visited.

• Generated in several ways, most common occurs when a Web

page includes content from multiple sources.

• DoubleClick

– IP address where content was delivered.

– Records data in cookie log.

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Case Study 9: Hadoop the Cookie Cutter (cont'd)

• Third-party cookie owner has history of what was shown,

what ads clicked, and intervals between interactions.

• Cookie log contains data to show how you respond to ads

and your pattern of visiting various Web sites where ads

placed.

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FireFox Collusion

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Ghostery in Use (ghostery.com)

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