DescriptionFULL NAME: _________________________________________________
BSAN310
SPRING 2023
Exam 1
INSTRUCTIONS
Write your name at the top of the page.
This exam has three (3) essay questions. The total points for the exam is 100 points.
Before beginning to write your answer, it is useful to step back and consider what your main
points will be and to establish an outline of your thoughts.
Ensure you answer the questions. With essay exams, students frequently will not answer the
question; they will veer off from the subject. Keep referring back to what the question is
asking and ensure your essay is focused on it. If there are multiple parts to the question,
ensure you thoroughly answer all parts of the question.
This is an open book/open notes exam.
Once you submit your exam in Canvas, please ensure it is actually submitted.
Section Exam 1 Open From: Tues Mar 7th –Fri Mar 10th (11:59pm)
EXAM INTENT: The intent of this exam is for you to demonstrate proficient command
of the subject matter in the course thus far. Your answers should show depth in your
ability to apply course content and concepts to practical examples. Moreover, your
answers should demonstrate a level of critical thinking demonstrating a strategic
viewpoint of business analytics and data topics/concepts leading you to logical
conclusions.
The Exam Begins on the Next Page
Page 1 of 2
1. (This question is based on our Module 1 and Module 2 resources). Your CEO wants
you to prepare a report for the Board of Directors that will attempt to convince them of
the importance and benefits of business analytics and data as a strategic asset to your
company. Specifically, your report must:
a. Explain what the term “Data Driven Decision Making” means;
b. Identify and thoroughly explain five (5) benefits a company can experience
with data driven decision making and with the use of data and business analytics;
and
c. Discuss at least two (2) examples of companies that practice data driven
decision making and that use data for competitive advantage…ensure you clearly
explain what these companies are doing with data and business analytics that is
beneficial for them.
2. Write an essay that accomplishes the following:
a. Define the term predictive analytics;
b. Thoroughly explain how predictive analytics can benefit a company; and
c. Define what the term data silo means and how data silos can cause problems
with an organization’s business analytics processes.
3. One outcome of business analytics in organizations is the concept of data
monetization. Write an essay that accomplishes the following:
a. Define what the concept of data monetization means including categories of
data monetization;
b. Thoroughly describe how you could use data wrapping–wrapping information
around core products and services, in a business. Identify and describe two (2)
examples of data wrapping.
Page 2 of 2
BSAN310
Introduction To Business Analytics
Brian R. Salmans
Objectives for Today
▪ Consider the Data aspect of business analytics
▪ Focus on data-driven decision-making
▪ How data management supports business analytics
▪ Importance of data to organizations: Data has value not just a
supporting role in organizations
▪ In-Class Exercise: Applying Concepts
March 9, 2023
Add Footer information here
2
What Is The Connection With Data Management?
March 9, 2023
Add Footer information here
3
Data-Driven Decision-Making
▪A primary goal of business analytics
▪Data driven decision making (DDDM) is the
process of using data to make informed and
verified decisions
(Why Data Driven Decision Making is Your Path To Business Success)
▪Incorporating data for decisions instead of
only reliance on the gut feeling or emotions
or experience
March 9, 2023
Add Footer information here
4
Organizations need to realize that data has value
▪ Research conducted by the Sloan School of Business indicates
that companies that engaged in data-driven decision-making
experience a 6% increase in the productivity and the output of
the company over the companies that do not.
March 9, 2023
Add Footer information here
5
How To Focus On Data…What Is Involved?
▪ 1. SOURCE THE DATA
▪ 2. WEIGH THE COSTS AND BENEFITS
▪ 3. SECURE OWNERSHIP OF THE DATA
▪ 4. MANAGE THE DATA
▪ 5. ESTABLISH INFRASTRUCTURE AND TECHNOLOGY
March 9, 2023
Add Footer information here
6
1. Source the Data/Securing Ownership
▪ Where do organizations get data?
▪ Internal
▪ External
▪ Collecting that data exhaust…
March 9, 2023
Add Footer information here
7
March 9, 2023
Add Footer information here
8
Data Brokers
March 9, 2023
Add Footer information here
9
How To Focus On Data…
▪ 1. SOURCE THE DATA
▪ 2. WEIGH THE COSTS AND BENEFITS
▪ 3. SECURE OWNERSHIP OF THE DATA
▪ 4. MANAGE THE DATA
▪ 5. ESTABLISH INFRASTRUCTURE AND TECHNOLOGY
March 9, 2023
Add Footer information here
10
2. Weigh the costs and benefits
▪ Identify the costs
▪ Is this straight forward?
▪ Direct costs/indirect costs
▪ SSNs
▪ Health data
▪ Access, who uses, controls…
▪ (more on this later with security/privacy and legal environment of data)
▪ Consider the expected benefits
▪ Competitive advantage
▪ Productivity
▪ Costs of data include security/privacy protections
March 9, 2023
Add Footer information here
11
March 9, 2023
Add Footer information here
12
How To Focus On Data…
▪ 1. SOURCE THE DATA
▪ 2. WEIGH THE COSTS AND BENEFITS
▪ 3. SECURE OWNERSHIP OF THE DATA
▪ 4. MANAGE THE DATA
▪ 5. ESTABLISH INFRASTRUCTURE AND TECHNOLOGY
March 9, 2023
Add Footer information here
13
3. Secure Ownership of the Data
• Data ownership refers to both the possession of
and responsibility for information. Ownership
implies power as well as control.
• The control of information includes not just the
ability to access, create, modify, package, derive
benefit from, sell or remove data, but also the right
to assign these access privileges to others
• Issues such as privacy, ethics, intellectual property,
legal environment (GDPR, data localization)…
March 9, 2023
Add Footer information here
14
Data Localization/Data Residency
▪Data localization is the practice of keeping data
within the region it originated from—the practice of
storing and processing data in the same country
where you originally collected it.
▪Certain regulations require this, including the EU
General Data Protection Regulation (GDPR), Brazil’s
General Data Protection Law (LGPD), and several
others (E.g. China, Russia, and India).
March 9, 2023
Add Footer information here
15
How To Focus On Data…
▪ 1. SOURCE THE DATA
▪ 2. WEIGH THE COSTS AND BENEFITS
▪ 3. SECURE OWNERSHIP OF THE DATA
▪ 4. MANAGE THE DATA
▪ 5. ESTABLISH INFRASTRUCTURE AND TECHNOLOGY
March 9, 2023
Add Footer information here
16
Data Life Cycle: Key to Data Management
March 9, 2023
Add Footer information here
17
Data Silos:
March 9, 2023
Add Footer information here
18
Stove Pipe or Silo Data
▪ Stove pipe/Silo–to develop, or be developed, in an isolated
environment; to solve narrow goals/problems or meet specific
needs in a way not readily compatible with other systems.
▪ (e.g. Alumni data vs. Business school data)
▪ A mindset present when certain departments or sectors do not
wish to share information with others in the same company
March 9, 2023
Add Footer information here
19
Stove Pipe or Silo Data
• These restrict the flow of information
• Breakdown or connect silos (think about networks
not hierarchies)
March 9, 2023
Add Footer information here
20
Managing the Data
▪ Difficulties of Managing Data.
▪ Amount of data increases exponentially.
▪ Data are scattered and collected by many individuals using various
methods and devices.
▪ Data come from many sources including internal sources, personal
sources and external sources.
▪ Data security, quality and integrity are critical.
▪ Data classification (next slide)
▪ Legal & ethical considerations, security, privacy, data
localization laws, think about data silos (breaking them down or
connecting them)
March 9, 2023
Add Footer information here
21
Ten Years After 9/11: A Status Report On
Information Sharing
▪ Ten years ago, our law enforcement and intelligence
communities were driven by a Cold War “need to know” culture
that stovepiped information and stymied cooperation. As
demonstrated by the ten lost “operational opportunities” to
derail the September 11th attacks that the 9/11 Commission
identified, both the CIA and the FBI failed to disseminate
information in the run-up to the attacks.
▪ Silos also existed between agencies and within individual
agencies
Data management issues: Data classification,
data silos
March 9, 2023
Add Footer information here
22
March 9, 2023
Add Footer information here
23
March 9, 2023
Add Footer information here
24
In-Class Assignment
• Choose one example of business analytics practiced by a company
in the article Competing On Analytics or The Challenges of Business
Analytics: Success and Failures. Then answer the following
questions and submit your answers in Word. You make work with
a partner.
• What is your example?
• What did the business gain from their business analytics efforts?
• What process did they improve?
• A business process is:
• A collection of related activities that create a product or service of
value to the organization, its business partners, and/or its customers.
• A standardized set of activities that accomplish a specific task or
goal
March 9, 2023
Add Footer information here
25
March 9, 2023
Add Footer information here
26
BSAN310
Introduction To Business Analytics
Brian R. Salmans
Objectives for Today
▪ Data Management
▪ Application of concepts
March 9, 2023
Add Footer information here
2
Data-Driven Decision-Making
▪A primary goal of business analytics
▪Data driven decision making (DDDM) is the
process of using data to make informed and
verified decisions
(Why Data Driven Decision Making is Your Path To Business Success)
▪Incorporating data for decisions instead of
only reliance on the gut feeling or emotions
or experience
March 9, 2023
Add Footer information here
3
How To Focus On Data…
▪ 1. SOURCE THE DATA
▪ 2. WEIGH THE COSTS AND BENEFITS
▪ 3. SECURE OWNERSHIP OF THE DATA
▪ 4. MANAGE THE DATA
▪ 5. ESTABLISH INFRASTRUCTURE AND TECHNOLOGY
March 9, 2023
Add Footer information here
4
Data Life Cycle: Key to Data Management
March 9, 2023
Add Footer information here
5
Data Classification…Why Is This Important?
https://policy.ku.edu/IT/data-classification-handling
March 9, 2023
Add Footer information here
6
Managing the Data
▪ Difficulties of Managing Data.
▪ Amount of data increases exponentially.
▪ Data are scattered and collected by many individuals using various
methods and devices.
▪ Data come from many sources including internal sources, personal
sources and external sources.
▪ Data security, quality and integrity are critical.
▪ Data classification (next slide)
▪ Legal & ethical considerations, security, privacy, data
localization laws, think about data silos (breaking them down or
connecting them)
March 9, 2023
Add Footer information here
7
How To Focus On Data…
▪ 1. SOURCE THE DATA
▪ 2. WEIGH THE COSTS AND BENEFITS
▪ 3. SECURE OWNERSHIP OF THE DATA
▪ 4. MANAGE THE DATA
▪ 5. ESTABLISH INFRASTRUCTURE AND TECHNOLOGY
March 9, 2023
Add Footer information here
8
5. ESTABLISH INFRASTRUCTURE AND
TECHNOLOGY
▪ The three key areas to consider when establishing your
infrastructure are:
▪ Creating tools and processes to access internal and external data;
▪ Ensuring that the processes involved in storing the data are safe; and
▪ Secure and in setting up data algorithms to analyze the data
automatically.
▪ Cloud computing
▪ Technology to support secure access to data (VPNs, 2FA…)
March 9, 2023
Add Footer information here
9
Big Data: An Overview
▪ SAS describes Big Data as “a term that describes the large
volume of data – that inundates a business on a day-to-day basis.”
▪ “The ever increasing amount of digital information being
generated and stored”
▪ “What’s important to keep in mind about Big Data is that the
amount of data is not as important to an organization as the
analytics that accompany it.”
▪ “When companies analyze Big Data, they are using Business
Analytics to get the insights required for making better business
decisions and strategic moves (the oil metaphor)”
March 9, 2023
Add Footer information here
10
Big Data
▪Big data refers to massive amounts of business
data from a wide variety of sources, much of which is
available in real time, and much of which is uncertain
or unpredictable.
▪“The effective use of big data has the potential to
transform economies, delivering a new wave of
productivity growth and consumer surplus. Using big
data will become a key basis of competition for
existing companies, and will create new competitors
who are able to attract employees that have the
critical skills for a big data world.”
▪ – McKinsey Global Institute, 2011
March 9, 2023
Add Footer information here
11
Big Data
March 9, 2023
Add Footer information here
12
Volume, Variety, Velocity
▪ “The 3Vs (volume, variety and velocity) are three defining
properties or dimensions of big data.”
▪ Volume—large amounts of data…must be able to process it.
▪ scalable storage and a distributed approach
▪ Variety—A common theme in big data systems is that the
source data is diverse, and doesn’t fall into neat relational
structures. It could be text from social networks, image data, a
raw feed directly from a sensor source
▪ Velocity—the increasing rate at which data flows into an
organization
March 9, 2023
Add Footer information here
13
Volume
▪ Volume. Organizations collect data from a variety of sources,
including business transactions, social media and information
from sensor or machine-to-machine data. In the past, storing it
would’ve been a problem – but new technologies (such as
Hadoop) have eased the burden.
March 9, 2023
Add Footer information here
14
Volume (Scale)
▪ Data Volume
▪ 44x increase from 2009 to 2020
▪ From 0.8 zettabytes to 35zb
▪ Data volume is increasing exponentially
Exponential increase in
collected/generated data
15
Variety
▪ Variety. Data comes in all types of formats – from structured,
numeric data in traditional databases to unstructured text
documents, images, email, video, audio, stock ticker data and
financial transactions.
March 9, 2023
Add Footer information here
16
Variety (Formats, Complexity)
▪ Relational Data (Tables/Transaction/Legacy
Data)
▪ Text Data (Web)
▪ Graph Data
▪ Social Network, Semantic Web (RDF), …
▪ Streaming Data
▪ You can only scan the data once
▪ A single application can be
generating/collecting many types of data
▪ Big Public Data (online, weather, finance, etc)
To extract knowledge➔ all these
types of data need to linked
together
17
Velocity
▪ Velocity. Data streams in at an unprecedented speed and
must be dealt with in a timely manner. RFID tags, mobile apps,
www click traffic, sensors and smart metering are driving the
need to deal with torrents of data in near-real time.
March 9, 2023
Add Footer information here
18
Velocity (Speed, Data Streams)
▪ Data is begin generated fast and need to be processed fast
▪ RFID, sensors, cell phones, internet of things…
▪ Online Data Analytics
▪ Late decisions ➔ missing opportunities
▪ Examples
▪ E-Promotions: Based on your current location, your purchase
history, what you like ➔ send promotions right now for store
next to you
▪ Healthcare monitoring: sensors monitoring your activities and
body ➔ any abnormal measurements require immediate
reaction
19
What Has Changed?
▪ LESS:
▪ Limitations on data gathering
▪ Limitations on data storage
▪ Limitations on data processing
▪ Limitations on analytical techniques
▪ Statistics, data tool, visualization…
March 9, 2023
Add Footer information here
20
How Big Data Is Changing Insurance Forever article
▪ An insurance business is made or broken on its ability to
accurately assess the risk posed by a particular driver and offer
them a competitive, but profit-making premium.
▪ Sources of data:
▪ You (car description, use/miles driven…)
▪ Department of Motor Vehicles (DMV) – driving history, claims,
▪ Credit Report (FICO Score from Credit Bureaus–Experian, Equifax
and TransUnion)
▪ Telematics–wireless telematics devices and “black box” technologies
that collect and transmit data on vehicle use, maintenance
requirements and automotive servicing (device or phone app)
▪ State Regulators
March 9, 2023
Add Footer information here
21
How Big Data Is Changing Insurance
Forever article…Advantages:
▪Better customer service
▪More efficiently priced premiums
▪A reduction in the overall harm caused by fraud
March 9, 2023
Add Footer information here
22
How Big Data Is Changing Insurance
Forever article…Fraud Detection:
▪How fraud is reduced
▪ Point of Sale Fraud (compare what is reported to data sources)
March 9, 2023
Add Footer information here
23
March 9, 2023
Add Footer information here
24
How Big Data Is Changing Insurance
Forever article
▪ Analysis of internal and external unstructured data provides a
great opportunity to uncover complex fraudulent activities,
which are difficult to trace through analysis of the structured
data. For instance:
▪ Scanning through social media interactions of a claimant may
reveal his visit to a bar before his car accident
▪ Applying analytics on claimant’s social network data may reveal his
connection with entities who are/were involved in fraudulent
activities
▪ Log notes and web interactions can confirm claimant’s urgency for
claim settlement, adjustor’s notes may point out inflated vehicle
repairs
March 9, 2023
Add Footer information here
25
How Big Data Is Changing Insurance Forever article
▪ Volume, Variety (type), Velocity (speed, near real-time)
▪ Ethics, privacy, healthcare information, information on
minors/children
March 9, 2023
Add Footer information here
26
▪ https://www.google.com/search?q=video+what+is+a+credit+sc
ore&rlz=1C1GCEA_enUS967US967&oq=video+what+is+a+cre
dit+score&aqs=chrome..69i57j33i160j33i299l2j33i22i29i30l6.59
53j0j15&sourceid=chrome&ie=UTF8#fpstate=ive&vld=cid:449fcc79,vid:dwIGfhhgKOc
March 9, 2023
Add Footer information here
27
Application: Credit Score
▪ Credit scoring is a predictive analysis of a consumer’s credit report
information, used to determine a consumer’s creditworthiness.
Businesses use credit scoring systems to make financing decisions,
market to new customers, maintain accounts, and create financial
projections.
▪ To create a credit scoring model, developers look for patterns and
trends within a sample of consumer data to determine risk
characteristics. Those characteristics are broken down into specific
attributes and assigned points to indicate whether the attribute has
a good or bad outcome. Attributes include things like:
• Total number of accounts in good standing
• Total number of mortgage accounts, or
• Average balance on the consumer’s credit cards.
March 9, 2023
Add Footer information here
28
What affects a business credit score?
▪ Several factors are used to determine business credit scores.
• Credit history. Business credit reporting agencies look to see how old a business is
when determining its score. Older businesses with long histories of financial stability
get better scores than newer businesses.
• Payment history. If a business has had any missed or late payments, that will reduce
its credit score. Even a single late payment can have a significant effect.
• Debt utilization. Debt utilization is the ratio of credit used by a business to credit
available to a business. Establishing sustainable business cash flow and taking on as
little debt as possible can help improve your score.
• Public records. Past bankruptcies, collections notices, liens, and other indications of
difficulty making payments can all count against your credit score.
• Demographic information. Credit bureaus will also make judgments about the
financial health of a business based on its industry risk, location, and size.
• Business failure score. This is a measurement of the risk your business will go
bankrupt in the next 12 months. Credit bureaus factor it in when calculating credit
scores.
▪
March 9, 2023
Add Footer information here
29
▪ A business credit score is a credit rating that signals the likelihood a
business will repay its loans on time and not default. Lenders rely
heavily on business credit scores to determine loan eligibility and
interest rates.
March 9, 2023
Add Footer information here
30
“Automate credit decisions and improve onboarding efficiency
with Decision Maker. Combine your credit policies with the world’s
largest set of business data and analytical insights from the Dun &
Bradstreet Data Cloud to help pre-screen and validate applicants,
and use custom credit scorecards to make instant decisions on
credit requests.”
March 9, 2023
Add Footer information here
31
March 9, 2023
Add Footer information here
32
Purchase answer to see full
attachment
