[Recommended] - KroenkeBoyle_UMIS12e_ppt_03.pptx

Using M I S
Twelfth Edition
Chapter 3
Business Intelligence Systems

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Study Questions
Q3-1 How do organizations use business intelligence (B I) systems?
Q3-2 How do organizations use data warehouses and data marts to acquire data?
Q3-3 What are three techniques for processing B I data?
Q3-4 What are the alternatives for publishing B I?
Q3-5 Why is artificial intelligence (A I) important?
Q3-6 How will A I and automation affect organizations?
Q3-7 What is the goal of A I?
Q3-8 How does A I work?
Q3-9 2031?

This chapter considers BI systems to identify patterns, relationships, and other information in organizational structured and unstructured social data, as well as purchased external data.
As you will learn, business intelligence is the key technology supporting marketing technology.
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Figure 3-1 Components of a Business Intelligence System
Q3-1 How do organizations use business intelligence (B I) systems?

BI systems are information systems that process operational and other data to identify patterns, relationships, and trends for use by business professionals and other knowledge workers.
Five standard IS components are present in BI systems: hardware, software, data, procedures, and people.
The boundaries of BI systems are blurry.
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Table 3-2 Types of Business Intelligence Systems
Q3-1 How do organizations use business intelligence (B I) systems?
Task
Grocery Store Example
Informing
Which products are selling quickly?Which products are most profitable?
Deciding
Which customers shop at each location?Create custom marketing plans per store.
Problem Solving
How can we increase sales?How can we reduce food waste?
Project Management
Build in-store cafés.Expand to other locations.

Use BI for all of the collaborative tasks described in Chapter 7.
eHermes could use BI to determine routes for its vehicles.
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Figure 3-3 Three Primary Activities in the B I Process
Q3-1 How do organizations use business intelligence (B I) systems?

Push publishing delivers business intelligence to users without any request from the users; the BI results are delivered according to a schedule or as a result of an event or particular data condition. Pull publishing requires the user to request BI results.
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Using Business Intelligence to Find Candidate Parts for 3D Printing
Q3-1 How do organizations use business intelligence (B I) systems?
Identify parts that might qualify.
Provided by vendors who make part design files available for sale
Purchased by larger customers
Frequently ordered parts
Ordered in small quantities
Use part weight and price surrogates for simplicity.

As shown in the next slide, the sales data is extracted from its IS department and stored it in Microsoft Access
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Figure 3-4 Sample Extracted Data
Q3-1 How do organizations use business intelligence (B I) systems?

IS department extracted the data. This table is a combination of data from the Sales table (CustomerName, Contact, Title, Bill Year, Number Orders, Units, Revenue, Source, PartNumber) and the Part table (PartNumber, Shipping Weight, Vendor) for select vendors willing to release 3D part design files.
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Figure 3-5 Customer Summary
Q3-1 How do organizations use business intelligence (B I) systems?

Source: Windows 10, Microsoft Corporation.

Customer summary displayed in Access.
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Figure 3-6 Qualifying Parts Query Results
Q3-1 How do organizations use business intelligence (B I) systems?

Source: Windows 10, Microsoft Corporation.

Publish query results is the last activity in the BI process.
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Figure 3-7 Sales History for Selected Parts
Q3-1 How do organizations use business intelligence (B I) systems?

Source: Windows 10, Microsoft Corporation.

Judging just by the results, there seems to be little revenue potential in selling designs for these parts.
It is possible they chose the wrong criteria.
Might find themselves changing criteria until they obtain a result they want, which results in a very biased study.
Importance of the human component of an IS: Business intelligence is only as intelligent as the people creating it!
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Using Data Warehouses and Data Marts to Acquire Data
Q3-2 How do organizations use data warehouses and data marts to acquire data?
Functions of a data warehouse
Obtain data
Cleanse data
Organize and relate data
Catalog data

For a small organization, the extraction may be as simple as an Access database. Larger organizations, however, typically create and staff a group of people who manage and run a data
warehouse, which is a facility for managing an organization’s BI data.
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Figure 3-8 Components of a Data Warehouse
Q3-2 How do organizations use data warehouses and data marts to acquire data?

This figure shows the components of a data warehouse. Programs read operational and other data and extract, clean, and prepare that data for BI processing.
An organization might use Oracle for its operational processing but use SQL Server for its data warehouse. Other organizations use SQL Server for operational processing but use DBMSs from statistical package vendors such as SAS or SPSS in the data warehouse.
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Figure 3-9 Examples of Consumer Data That Can Be Purchased
Q3-2 How do organizations use data warehouses and data marts to acquire data?
Name, address, phone
Age
Gender
Ethnicity
Religion
Income
Education
Voter registration
Home ownership
Vehicles
Magazine subscriptions
Hobbies
Catalog orders
Marital status, life stage
Height, weight, hair and eye color
Spouse name, birth date
Children’s names and birth dates

Purchasing data about other organizations is not unusual or particularly concerning from a privacy standpoint.
Some companies choose to buy personal consumer data (like marital status) from data vendors like Acxiom Corporation.
Ask students if they are surprised by the amount and types of information that are available.
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Figure 3-10 Possible Problems with Source Data
Q3-2 How do organizations use data warehouses and data marts to acquire data?
Dirty data
Missing values
Inconsistent data
Data not integrated
Wrong granularity
Too fine
Not fine enough
Too much data
Too many attributes
Too many data points

Operational and purchased data has problems that inhibit its usefulness for business intelligence.
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Figure 3-11 Data Mart Examples
Q3-2 How do organizations use data warehouses and data marts to acquire data?

The data analysts who work with a data warehouse are experts at data management, data cleaning, data transformation, data relationships, and the like. However, they are not usually experts in each business function.
A data mart is a subset of a data warehouse. A data mart addresses a particular component or functional area of the business.
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Table 3-12 Differences Between DataWarehouses and Data Lakes
Q3-2 How do organizations use data warehouses and data marts to acquire data?
Data Type
Data Warehouse
Data Lake
Data Structure
Structured data
Structured and unstructured data
Data Structure
Cleaned and filtered data
Raw data
Data Structure
Historical data
Historical and real-time data
Data Structure
Operational systems and purchased data
Operational systems, purchased data, smart devices, clickstreams, social media posts, images, etc.
Users
Used by business analysts
Used by data scientists

A data lake is a central repository for large amounts of raw unstructured data. Data lakes are similar to data warehouses, but they are used for different purposes.
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Table 3-13 Three Types of B I Analysis
Q3-3 What are three techniques for processing B I data?
B I Analysis Type
Goal
Characteristics
Reporting
Create information about past performance
Process structured data by sorting, grouping, summing, filtering, and formatting
Data mining
Classify and predict
Use sophisticated statistical techniques to find patterns and relationships
Big Data
Find patterns and relationships in Big Data
Volume, velocity, and variety force use of MapReduce techniquesSome applications use reporting and data mining as well

This figure summarizes the goals and characteristics of three fundamental types of BI analysis. In general, reporting analyses are used to create information about past performance, whereas data mining is used primarily for classifying and predicting.
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Figure 3-13 Example R F M Scores
Q3-3 What are three techniques for processing B I data?
How recently (R) a customer has ordered
How frequently (F) a customer ordered
How much money (M) the customer has spent

RFM analysis is a technique readily implemented with basic reporting operations that is used to analyze and rank customers according to their purchasing patterns.
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Figure 3-15 Example Grocery Sales O L A P Report
Q3-3 What are three techniques for processing B I data?

Online analytical processing (OLAP) is more generic than RFM and provides the ability to sum, count, average, and perform other simple arithmetic operations on groups of data.
An OLAP report has measures and dimensions.
A measure is the data item of interest. It is the item that is to be summed or averaged or otherwise processed in the OLAP report. Total sales, average sales, and average cost are examples of measures.
A dimension is a characteristic of a measure. Purchase date, customer type, customer location, and sales region are all examples of dimensions.
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Figure 3-16 Example of Expanded Grocery Sales O L A P Report
Q3-3 What are three techniques for processing B I data?

OLAP reports are dynamic and the viewer of the report can change the report’s format.
This figure shows such an alteration. The user added another dimension, Store Country (nested row under Product Family) and Store State (nested row under Store Country), to the horizontal display. Product-family sales are now broken out by store location
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Figure 3-17 Example of Drilling Down into Expanded Grocery Sales O L A P Report
Q3-3 What are three techniques for processing B I data?

Drilling down into data means to further divide the data into more detail.
This figure shows that the user has drilled down into the stores located in California; the OLAP report now shows sales data for the four cities in California that have stores
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Figure 3-18 Source Disciplines of Data Mining
Q3-3 What are three techniques for processing B I data?

To find patterns and relationships among data, more user-friendly processes have been developed to allow users to visually analyze and explore data. This process is called data discovery. Data visualization, or the graphical representation of data, allows users to quickly understand complex data.
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Unsupervised Data Mining
Q3-3 What are three techniques for processing B I data?
Does not use a priori hypothesis or model
Findings obtained solely by data analysis
Hypothesized model created to explain patterns found
Example: Cluster analysis

Cluster analysis: Statistical technique to identify groups of entities with similar characteristics; used to find groups of similar customers from customer order and demographic data.
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Supervised Data Mining
Q3-3 What are three techniques for processing B I data?
Uses a priori model
Prediction, such as regression analysis
Ex: CellPhoneWeekendMinutes

Predict number of minutes of weekend cell phone use
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Using Big Data Applications
Q3-3 What are three techniques for processing B I data?
Huge volume – petabyte and larger
Rapid velocity – generated rapidly
Great variety
Structured data, free-form text, log files, graphics, audio, and video

Big Data is a term used to describe data collections that are characterized by huge volume, rapid velocity, and great variety.
A data set containing all Google searches in the United States on a given day is Big Data in size.
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Figure 3-19 MapReduce Processing Summary
Q3-3 What are three techniques for processing B I data?
Map Phase: Google search log broken into thousands of pieces

MapReduce is a technique for employing the power of thousands of computers working in parallel.
A Big Data collection is broken into pieces, and hundreds or thousands of independent processors search these pieces for something of interest.
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Hadoop
Q3-3 What are three techniques for processing B I data?
Open-source program supported by Apache Foundation
Manages thousands of computers
Amazon supports Hadoop as part of EC3 cloud
Hadoop includes the query language named Pig
Hadoop requires experts to use it

Figure 3-20 Google Trends on the Terms Web 2.0 and Hadoop
Q3-3 What are three techniques for processing B I data?

This trend line supports contention that “Web 2.0” is fading from use.
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Table 3-20 B I Publishing Alternatives
Q3-4 What are the alternatives for publishing B I?
Server
Report Type
Push Options
Skill Level Needed
Email or collaboration tool
Static
Manual
Low
Web server
Static/Dynamic
Alert/RSS
Low for static High for dynamic
SharePoint
Static/Dynamic
Alert/RSS Workflow
Low for static High for dynamic
B I server
Dynamic
Alert/RSS Subscription
High

In the BI context, most static reports are published as PDF documents. Dynamic reports are BI documents that are updated at the time they are requested. A sales report that is current at the time the user accessed it on a Web server is a dynamic report.
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Figure 3-22 Elements of a B I System
Q3-4 What are the alternatives for publishing B I?

A BI server is a Web server application that is purpose-built for the publishing of business intelligence and provides two major functions: management and delivery.
The management function maintains metadata about the authorized allocation of BI results to users and tracks what results are available, which users are authorized to view those results, and the schedule upon which the results are provided to the authorized users.
The delivery function uses metadata to determine what results to send to which users, on which schedule, and can be delivered to “any” device.
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Knowledge Management Systems
Q3-4 What are the alternatives for publishing B I?
Knowledge Management (K M)
Creates value from intellectual capital and shares knowledge with those who need that capital
Improves process quality
Increases team strength
Goal: Enable employees to use organization’s collective knowledge

Resistance to Knowledge Sharing
Q3-4 What are the alternatives for publishing B I?
Employees reluctant to exhibit their ignorance
Employee competition
Remedy
Strong management endorsement
Strong positive feedback
“Nothing wrong with praise or cash . . . especially cash.”

Strong management endorsement can be effective in encouraging knowledge sharing, especially if that endorsement is followed by strong positive feedback.
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What Are Content Management Systems (C M S)?
Q3-4 What are the alternatives for publishing B I?
Support management and delivery of documents and other expressions of employee knowledge
Challenges of Content Management
Huge databases
Dynamic content
Documents refer to one another
Perishable contents
In many languages

Content management system functions are huge and complex.
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What is A I?
Q3-5 Why is artificial intelligence (A I) important?
Artificial intelligence (A I)—ability of a machine to simulate human abilities such as vision, communication, recognition, learning, and decision making in order to achieve a goal
A I could be used in robots, commercial drones, agricultural systems, military platforms, surgical systems, and other smart devices

Figure 3-23 Forces Driving A I Innovation
Q3-5 Why is artificial intelligence (A I) important?

This figure shows the six main forces that have helped advance AI in recent years.
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Table 3-24 Examples of Practical A I Applications
Q3-5 Why is artificial intelligence (A I) important?
Company
Practical Artificial Applications
Amazon
Alexa, Echo, Amazon Rekognition, Amazon Polly, Amazon Lex, Amazon Machine Learning, Amazon E M R, Spark & Sparkml, A W S Deep Learning A M I
Facebook
DeepText, DeepFace, News Feed, targeted advertising, filtering offensive content, search rankings, application design
Google
Google Assistant, Google Translate, Home, Google Brain, TensorFlow, Cloud ML, DeepMind Lab, Convnet.js, OpenFrameworks, Wekinator.
Microsoft
Cortana, Computer Vision, Face, Content Moderator, Translator Speech, Translator Text, Language Understanding Intelligent Service, Recommendations, Q n A Maker, Bing Image Search, Integrated into Microsoft Suite.
Apple
Integrated into all Apple products and services (Siri, iPhone, HomePod, iWatch, etc.)

Figure 3-25 Employee Costs Per Hour (U.S.)
Q3-6 How will A I and automation affect organizations?

Table 3-26 Benefit of Automated Labor Versus Human Labor
Q3-6 How will AI and automation affect organizations?
Benefits of Automated Labor
Benefits of Human Labor
1. Work 24 hours a day, 365 days a year
1. Unique problem solving
2. No scheduling issues, all holiday shifts covered
2. Create new products
3. No time off, breaks, or sick days
3. Adaptable to rapidly changing environment
4. No impaired workers, drinking on the job, or illicit drug use
4. Integrative systems thinking
5. Safer work environment: no accidents, injuries, sexual harassment, workman’s compensation claims
5. Question poorly made decisions
6. No unions, arguments, complaints, bad attitudes, employee lawsuits, layoffs, severance packages
6. Prior experience to predict future events
7. No healthcare, Social Security, unemployment, insurance, or retirement expenses
7. Ethical decision making (hopefully)
8. No minimum wage, raises, bonuses, overtime, or paychecks.
8. Interact well with humans (e.g., sales, coworker morale)
9. More accurate, precise, and consistent work

10. No time-wasting activities

11. Immediately trained, no “onboarding”

Figure 3-27 Employee Fraud Frequency and Median Loss
Q3-6 How will A I and automation affect organizations?

This figure shows the type of employee fraud by frequency and median loss per incident. Not all types of fraud are the same. Some types of fraud, like financial statement fraud, don’t occur that often but have large median losses.
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How Will A I Affect You?
Q3-6 How will A I and automation affect organizations?
By 2030, 30% to 40% of work performing routine physical and mental tasks could be taken out of the current workforce
Workers will be replaced by robots with I Qs higher than 90% of the U.S. population
Unwanted dirty jobs will be done by AI and automation
Retraining and retooling of workers for new types of jobs

There are typically two distinct reactions to AI.
The first reaction is from the group of people who see AI as an incredible opportunity. They get excited about the gains in productivity, profitability, and competitive advantages.
The second reaction is from the group of people who see AI as a serious threat. They’re worried about their jobs and are concerned about what happens if they get replaced by a machine or an AI bot.
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Figure 3-28 Evolution of A I Abilities
Q3-7 What is the goal of A I?
Weak A I which is focused on completing a single specific task
Strong A I that can complete all of the same tasks a human can
Superintelligence capable of intelligence more advanced than human intelligence

Figure 3-29 Turing Test
Q3-7 What is the goal of A I?

An early computer scientist named Alan Turing said a machine could be considered intelligent if a human could have a conversation with it and not be able to tell if it was a machine or a human.
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Figure 3-30 Major A I Research Areas
Q3-7 What is the goal of A I?

This figure shows the major AI research areas that focus on different aspects of human abilities.
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Figure 3-31a Classifying Emails as Spam or Legitimate
Q3-8 How does A I work?

This figure shows how machine learning is used to automatically detect spam.
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Figure 3-31b Emails Containing the Word “Promotion”
Q3-8 How does A I work?

This figure shows how machine learning is used to detect spam containing the word protection.
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Figure 3-32 I B M’ s Question-And-Answer Process
Q3-8 How does A I work?

IBM’s artificial intelligence named Watson is a question answering system that draws on several areas of AI.
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Business Intelligence Systems in 2031
Q3-9 2031?
Data storage, processing power, and network speeds will increase exponentially
Your location, sleeping patterns, exercise routines, stress levels, and food preferences will be known
Singularity
Computer systems adapt and create their own software without human assistance.
Machines will possess and create information for themselves.
Will we know what the machines will know?

Capital One Data Breach
Security Guide
Massive breach at Capital One in July 2019
Capital One stored data in the cloud with Amazon Web Services (AWS)
Its data was compromised by a former AWS employee who downloaded the data of over 100 million credit card applications

The Capital One story is just one more in a string of high-profile cybersecurity incidents. Ask students if they have heard of other security breaches.
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Senior Business Systems Analyst (1 of 2)
Career Guide
Colton Mouritsen at Honeywell, Inc.
Q. What attracted you to this field?
A. “My path to this field is unlike most others in similar positions. I started out as an accountant and even received a Master’s in Taxation from Weber State University. During my 5-year stint in the accounting industry I learned a lot about myself and my career goals. I did not necessarily love the daily work and monotony of accounting, but I loved the side of my job where I was able to analyze data.”

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