Before Class
Don't sign in to anything. Get to know your neighbors.
Introductions
To one another, me, and LA
For how many semesters prior to this one have you been at FGCU?
How many courses are you taking this semester?
What is your level of experience and comfort with technology (1-4)?
Where do you currently live while going to school?
What is your major / minor / concentration?
Instructor introduction
Contact options
Roster check / Attendance
Name cards
Hands-On
Sign in to browser (Firefox with uBlock Origin recommended)
Bookmarks (and apps on phone)
Textbook
OneDrive
OneNote
Canvas
GenAI
ChatGPT
Copilot
Gemini
NotebookLM
Sign in to OneDrive app
Folder setup
Teams app / web site
Outlook Calendar
Bookings & Office hours
Introduction Discussion Preview / Review
Importance of closely reading and following instructions, checking rubric, resubmitting work
About the Course
Find the relevance for you
Exit Ticket
What level you chose (1-4)
Framing
“Today is about seeing the big picture. Not how to click buttons, but how information systems actually help businesses work, compete, and make better decisions. If you’ve ever thought ‘I’m not a tech person,’ today is designed to change that.”
Learning Objectives
By the end of class, students will be able to:
Explain what an information system is (and what it is not)
Distinguish IT vs. IS, data vs. information vs. knowledge
Identify core components of an information system
Apply systems thinking to explain how business outcomes emerge
Connect IS concepts to their major and future careers
Warm-Up Hook: “Invisible Systems” (8-10 min)
Mini-Concept Clarification (5 min)
A system is a set of parts or components working together towards a common goal.
Information systems contain interrelated components (technology, people, and process) that allow us to take and transform meaningless data into useful information for decision making.
A systems thinking approach looks at an entire process taking into consideration all of the parts in the system and how they work together instead of focusing on just one component.
Information System = People + Processes + Data + Technology → Information → Decisions
Systems Thinking in Action (25 min)
Systems Thinking Activity (Canvas Groups)
Debrief: Gen AI Insights (time permitting)
Graded Project Work Time (time permitting)
Wrap-Up & Confidence Close
Exit Question (verbal or written):
“One sentence: How is an information system more than just technology?”
Closing message (career-framed):
“Every business major here will work with information systems. You don’t need to build them, but you do need to understand them well enough to ask smart questions. That’s the skill we’re building.”
Previous Lesson Review
System
Information system
Systems thinking
Big Picture Goal
“Today is not about becoming AI experts.
It’s about learning how to talk about AI intelligently, question it responsibly, and use it productively as future business professionals.”
Learning Objectives
By the end of class, students will be able to:
Use AI-related terminology correctly in business conversation
Distinguish between AI myths and realities
Identify benefits, risks, and ethical concerns of AI
Write and improve a GenAI prompt
Explain where humans still matter most
Resource Review
What is AI?
Artificial Narrow Intelligence
Artificial General Intelligence
Artificial Super Intelligence
Machine Learning
Deep Learning
Natural Language Processing
AI and Careers
Copilot in Excel
Activity
Using GenAI
IBM SkillsBuild Artificial Intelligence Fundamentals Learning Plan
IBM SkillsBuild Getting Started with Artificial Intelligence Learning Plan
Emerging Technologies
Previous Lesson Review
Big Picture Goal
Learning Objectives
Chapter 2
Discuss the impacts of digital technology on the business landscape;
Explain how strategy is impacted by technology;
Describe the components of competitive advantage;
Outline the value chain concept;
Recognize the role technology can play in crafting an imitation-resistant value chain; and
Explain the danger of relying on technology.
Resource Review
Chapter 2
Activity
Strategic Information Systems Worksheet: start working on Group Case sections A and B and start thinking about Individual Case
Previous Lesson Review
Sourcing Strategy (The "Where") How does the business obtain and run this system?
On-Premise (Hardware/Software owned and managed in-house)
SaaS (Software as a Service - Ready-to-use via subscription)
PaaS/IaaS (Cloud infrastructure - You build / manage apps on rented servers)
Big Picture Goal
Learning Objectives
Chapter 3 - Hardware
Define digital devices;
Identify the primary components of a computer system and the functions they perform;
Explain the factors distinguishing computing power of computers;
Describe the types of input, output, and memory devices;
Discuss hardware trends including: mobile computing, integrating computing;
Assess the impact of commoditization of computers; and
Summarize the problem of e-waste.
Chapter 4 - Software
Define the term software;
Describe the two primary categories of software;
Discuss cloud computing and its advantages and disadvantages for use in an organization;
List the ways in which software can be obtained; and
Define the term open-source and identify its primary characteristics.
Resource Review
Hardware
Bits
Computer hardware kitchen analogy: the CPU is the chef (processing), RAM is the countertop (active workspace), and the hard drive is the pantry/fridge (long-term storage). The motherboard acts as the kitchen floor connecting everything, while the PSU is the electricity supplying the kitchen.
Moore’s Law isn't strictly true in its original form (doubling transistors every 1-2 years via simple shrinking), as physical limits are being reached, but it has been generalized into the concept that computing power will double every two years for the same price point.
Check your hardware
PC: Settings > System > About
Mac: Apple icon in the upper-left corner of the screen > About This Mac > Overview tab
Software
ERP - SAP
ERP, CRM, SCM, ECM, AI, OLAP, blockchain (more about enterprise software in chapter 11 and decision support software in chapter 12)
https://ecampusontario.pressbooks.pub/app/uploads/sites/2109/2021/11/database-1-768x768.png
https://www.vmware.com/topics/server-virtualization#how-it-works
Activity
Strategic Information Systems Worksheet: start working on Group Case section C and work on Individual Case
Blooket (time permitting)
Previous Lesson Review
Learning Objectives
From textbook
Define the term database;
Describe the role of a database management system;
Explain the difference between a relational and flat file database;
Outline the levels of the data hierarchy;
Describe the different data types;
Identify and apply the steps to create a simple relational database; and
Discuss the advantages of the database approach.
Conceptual Core
Enterprise Resource Planning System with database at center (ch. 11)
Active Learning
Start to design a database for your small business
Model the entities and relationships. What would be three main tables? What would would be the fields?
IS Strategy Data Worksheet
Start Relational Database Exercise - make sure you can open the file
Start LinkedIn Learning - make sure you can access
Resources
Modeling / Diagramming Tools
Visio - launch through web, on lab computer, VLab, or AppsAnywhere
Lucidchart - create an account and look at templates
Mongo
Automate common or repetitive tasks with Quick steps in Outlook
Overview of using Outlook and Power Automate Microsoft Learn
Power Automate
Write one scenario (use case) in which you can automate a task using GenAI to make your life easier. (Write in the first person!)
Sample prompt:
Act as a thoughtful Strategic IT Consultant supporting me as a college student at FGCU. Your goal is to interview me to help me discover a manual, repetitive task—a 'pain point'—that I can automate using GenAI and Power Automate to make my life easier.
Please follow these instructions:
Adopt a warm, motivational, and professional tone that builds my confidence in using technology.
Ask me one question at a time to avoid overwhelming me [previous turn context].
Focus on these four areas to uncover a use case:
Manual 'Busy Work': Tasks like copying data from emails into spreadsheets or manually sending reminders.
Data 'Blind Spots': Deciding things based on 'gut feeling' rather than having facts at my fingertips.
Scalability Issues: Systems that would 'break' if my workload doubled tomorrow (like a messy Excel list that should be a database).
Experience Gaps: Recurring questions I have to answer over and over again.
Once we identify a 'friction' point, help me explain why an automated workflow (like a Microsoft Form triggered to update a spreadsheet and send a confirmation email) is a feasible solution that supports 'Business Operations' or 'Service'.
Start the interview now by asking me about a task I do every week that feels like 'robotic' work.
Upon successful completion of this chapter, you will be able to:
Define the term business process;
Explain how business process management and business process re-engineering work and the associated advantages and disadvantages;
Identify the different systems needed to support business processes in an organization;
Explain transaction processing systems, and contrast them to enterprise systems; and
Outline how information technology combined with business processes can bring an organization competitive advantage.
Business Process - A process is a series of tasks that are completed in order to accomplish a goal. A business process, therefore, is a process that is focused on achieving a goal for a business.
Application (think / research then ask in your IS Strategy chat)
For your major industry leader and your individual case: What are some of their core business processes?
For your individual case:
What are some best practices for business process management that could benefit them?
What technology systems could help with this?
Which of these would be the best for a college student majoring in [your major] to learn more about and possibly help implement or re-engineer?
Tell me more about option [option # most interesting to you].
ERP
(will be reviewed in upcoming What Is SAP S/4HANA For Beginners? (5:40) video)
SAP
For your major industry leader: (research then ask in your IS Strategy chat)
What are some of their core business processes?
Does your major's industry leader company use SAP S/4HANA?
With what Value Chain Activity does it link?
How does it support the Four Pillars?
Pre video review: hardware (memory and hard drive), sourcing / deployment options (on premise and SaaS)
SAP Learning - Student Zone free courses
For your individual case: (think then ask in your IS Strategy chat)
Would your individual company benefit from ERP software?
Top Small Business ERP Systems (2026)
CRM
For your major industry leader: (research then ask in your IS Strategy chat)
What do they use for CRM?
With what Value Chain Activity does it link?
How does it support the Four Pillars?
For your individual case: (think then ask in your IS Strategy chat)
What do they or might they use for CRM? (plan to ask someone if you don't know)
Would they benefit from CRM software?
Top Small Business CRM Systems (2026)
Blockchain
For your major industry leader: (research then ask in your IS Strategy chat)
Does they use blockchain?
Hands-On ERP Exercise
Chrome is recommended
I recommend you keep a document open as you do it to save things like your username and password, created customer number, inquiry number, quotation number, sales order number, etc.
You can use the Copilot tool in Word if you have it or upload the instructions to GenAI to be able to ask questions
Kahoot (time permitting)
Upon successful completion of this chapter, you will be able to:
Define big data;
Describe the decision making process;
Distinguish between the types of decisions by organizational level and type;
Compare the different types of information systems used by management for decision making;
Discuss business intelligence, and the tools available to support decision making;
Discuss some considerations for data analysis projects;
Define data mining and describe its role in an organization; and
Describe the difference between a data warehouse and a data mart.
Big Data
The Three V's image
Practice making a decision (like what to eat for dinner) using the 6 steps
Decision Support Systems
For your major industry leader case: (research then ask in your IS Strategy chat)
What are some key business decisions that need to be made?
What kind of decision support systems do they use?
For your individual case: (think then ask in your IS Strategy chat)
What are some key business decisions that need to be made?
What data is available to help them make these decisions?
What kind of decision support systems might they use or benefit from?
How might an Excel Pivot Table help the business?
Analysis and Reporting Tools
The Two Most Important Quotes In Business
Think Pair Share: What is something you want to improve in your life and what can you do to measure it?
Excel Pivot Table
Introduction
Welcome to the Excel Pivot Table Exercise, a project designed to give you a professional edge by mastering one of the most critical skills required for business students. Whether you are going into Accounting, Marketing, or Supply Chain, the ability to transform a "mountain of data" into a clear business story is exactly where the high-paying jobs are found.
In today’s business world, managers cannot make smart decisions based on "gut feelings" alone; they must use facts. Pivot Tables are a type of Online Analytical Processing (OLAP) tool that allows you to "slice and dice" massive amounts of data to uncover hidden trends,.
Accountants use them to find discrepancies in thousands of transactions.
Marketers use them to see which gender or region is buying specific products.
Supply Chain Managers use them to analyze how store distance impacts annual spending,.
Most business data starts in an OLTP (Online Transaction Processing) database, which records daily activities like individual sales or time sheets. However, you cannot easily analyze data while people are still using it for sales.
To solve this, companies use a process called ETL (Extraction, Transformation, and Loading) to move data into a Data Warehouse. A data warehouse is a centralized, read-only "staging area" for historical data. For this assignment, you will take 750 rows of a retailer's customer data, recorded over five years across three regions, and act as the analyst to determine who is performing the best and why,.
This hands-on exercise will guide you through the "Lego logic" of building a report from scratch. You will learn to:
Drill-Down: Move from a single total spending number to a detailed view of performance by region and year,.
Slice-and-Dice: Flip the data to see it from different perspectives, such as comparing shopping patterns between male and female customers.
Calculate New Insights: Use formulas to find "Spending per Visit" rather than just total sums,.
Visualize the Story: Create a 2-D Line Chart to graphically present the relationships you discovered.
By the end of this exercise, you will have a Word document containing 9 specific screenshots of your analysis. This isn't just about clicking buttons; it's about building the technology agility and systems-thinking mindset that will set you apart in any job interview,.
For your industry leader, in your IS Strategy chat...
I see this company uses [System Name]. What are the most common cybersecurity risks associated with this specific software, and how does the company likely defend against them?
What are some cybersecurity regulations within this industry?
Industry Leader and Small Business Worksheet - Cybersecurity
Learning Outcomes
Define information ethics and explain the purpose of a code of ethics;
Identify the policies organizations should implement for information management;
Define intellectual property and discuss the issues related to the infringement of intellectual property;
Explain information privacy and outline the methods for improving the privacy of information;
Describe the digital divide and explain Nielsen’s three stages of the digital divide; and
Discuss other social impacts to information technology use.
Related to How data brokers sold my identity video
Madhumita Murgia’s Recent Work
The Business of Biometrics In 2019, Murgia gave a follow-up TEDx talk focusing on how data brokers have moved from "cookies" to "biological data." She explores how faces, voices, and DNA are now being traded, often without consent, leading to potential "digital colonialism" where the most vulnerable populations are mined for data to train AI models.
Code Dependent: Living in the Shadow of AI (Book Released 2024/2025): Now the AI Editor for the Financial Times, Murgia published a book as a direct sequel to her talk, moving from "who owns my data" to "how is this data being used by AI to make life-altering decisions."
Protecting Americans’ Data from Foreign Adversaries Act (2024): A major recent update is this federal law which empowers the FTC to stop data brokers from selling sensitive personal data to "foreign adversary" nations (like China or Russia). In early 2026, the FTC issued warnings to 13 major data brokers to comply or face heavy fines.
State-Level Privacy Wave: Since the talk, over 20 US states (including Texas, Florida, and California) have enacted comprehensive privacy laws. As of 2025, many of these now include the "Right to Know" which third-party recipients have your data and the "Right to Contest" adverse profiling decisions made by AI.
General Data Protection Regulation (GDPR) an EU law, an "opt-in" system where websites must ask permission first. This is why you need to accept cookies now.
Principles: lawfulness, fairness and transparency, purpose limitation, data minimization, accuracy, storage limitation, integrity and confidentiality, accountability
Global Privacy Control (GPC) a technical standard / tool, a "universal opt-out" signal often used to meet "Do Not Sell/Share" requirements in the United States
Global Privacy Control (GPC) for Businesses (7:51) for web developers
Ethics
The Trolley Dilemma
Real-life trial - The Greater Good - Mind Field S2 (Ep 1)
As a computer programmer for self-driving cars, if there were only the two choices, would you allow a car to hit 5 people crossing the street or program it to divert to the sidewalk and hit 1 person?
Discussion reminder
Project work
Review impact & selection
Do development
Start presentations / Canva training
GenAI Image and Video Development Exercise
Submitting to the Transferable Skills Digital Badge course
How to make PPTX file from Canvas and why
Rubric for essay
4 - ready to submit
3 - could submit but could be improved
2 - really should be improved before submitted
1 - do not submit
Your third artifact
IBM SkillsBuild Professional Skills
Effective Presentation and Communication (90 min)
Collaboration and Team Dynamics (120 min)
Interpersonal and Workplace Communication (90 min)
Agile Ways of Working (120 min)
Problem Solving and Critical Thinking (90 min)
SPoI
LA Recognition
LinkedIn connections
Late work deadline
1) What is an Information System (IS)?
IS Components: Technology + People + Process (how tech is used, by whom, to achieve outcomes).
Systems Thinking: Analyze the whole process and interdependencies (inputs → processing → outputs → feedback), not parts in isolation.
IS vs. IT: IS = socio‑technical system; IT = hardware/software/network tools used by IS.
2) Strategy & Competitive Analysis
VRIN/VRIO resources for sustainable advantage: Valuable, Rare, Inimitable (imperfectly imitable), Non‑substitutable.
Porter’s Five Forces: Industry rivalry, threat of entrants, threat of substitutes, buyer power, supplier power → assess industry attractiveness.
Porter’s Value Chain
Primary: inbound logistics, operations, outbound logistics, marketing/sales, service.
Support: firm infrastructure, HR management, technology development, procurement.
Porter’s Generic Strategies: Cost leadership, Differentiation, Focus (technology supports these; it isn’t a standalone generic strategy).
3) Hardware, Performance & E‑Waste
Performance drivers: CPU clock speed, motherboard bus speed, RAM transfer rate (all matter).
Rapid Obsolescence → E‑waste (environmental/ethical considerations).
4) Enterprise Systems & Software Choices
ERP: Integrates functions via a centralized database; embeds best practices; configurable/customizable; improves cross‑functional visibility.
Enterprise Systems: ERP, CRM, SCM (all are enterprise systems).
Build vs. Buy vs. Cloud (SaaS):
Proprietary/custom (build): fit + control; higher initial cost (not an advantage).
Off‑the‑shelf (buy): common needs + support; may include unneeded features.
Cloud computing advantages: no local installs, elastic scale, rapid deployment.
Cloud trade‑offs: third‑party reliance, internet required, auto‑upgrades can disrupt.
Virtualization: Run multiple VMs on one host → fewer physical servers, lower power/cooling.
5) Data, Databases & Big Data
DBMS: Software to create/store/maintain/access databases.
Relational vs. NoSQL: Relational can scale less well for rapid growth vs. NoSQL which scales horizontally.
Why Relational? Minimize redundancy, improve integrity, strengthen security/recovery.
Big Data (“3Vs”): Volume, Variety, Velocity (not “virtual”).
6) Networking Essentials
TCP/IP: Protocol suite enabling heterogeneous networks to interoperate (Internet foundation).
Extranet: Securely exposes part of a company’s internal network to partners (vs. intranet/internal, Internet/public).
P2P: Peers communicate without a central server.
Blockchain: Distributed, append‑only ledger across peers.
7) Systems Development
SDLC = Systems Development Life Cycle.
Classical Phases: preliminary analysis → analysis → design → programming → testing → implementation → maintenance.
“Waterfall” = linear, document‑heavy, late delivery.
Agile = small increments, frequent feedback, continuous quality.
8) Business Processes & Information Systems
BPM (Business Process Management): Plan → document → implement → monitor processes with IT support.
Common Systems:
TPS: captures transactions.
MIS: periodic, routine reports for managers (e.g., sales by region).
DSS: supports semi‑structured managerial decisions.
EIS/Executive: high‑level summaries for unstructured decisions.
OLAP vs. OLTP: OLAP users “slice & dice” and drill down; OLTP focuses on day‑to‑day transaction processing.
9) Security, Privacy & Ethics
CIA Triad: Confidentiality, Integrity, Availability.
Auth → Access Control: After verifying identity, authorize actions/resources.
Security Policy: Written guidelines for acceptable use, roles, controls, and regulatory duties.
Usability Trade‑off: Balance security vs. usability.
Code of Ethics: Defines acceptable professional behavior.
Fair Use: Limited use of copyrighted works for scholarship/commentary.
PII (Personally Identifiable Information): Identify, minimize collection/retention.
10) Digital Inclusion & E‑Commerce
Digital Divide: Gap between those with/without network access.
E‑commerce Advantages: 24×7 reach, broader markets, lower physical overhead, expanded offerings (most cases).
Ways to Launch an Online Store: Hosted e‑commerce platform; rent hosting + self‑manage; self‑host on own servers.
https://play.blooket.com/play?hwId=69af1f2d597488fadb1216c2
https://play.blooket.com/play?hwId=69af1f558a1fbce6edbb2b5a
1. Foundations of Artificial Intelligence
Artificial Intelligence (AI): The simulation of human intelligence in machines that can perform tasks such as reasoning, learning, and problem‑solving.
Turing Test: Measures whether a machine’s responses are indistinguishable from a human’s.
2. Types & Levels of AI
Narrow AI: Performs one specialized task (e.g., facial recognition).
General AI: A theoretical AI capable of human‑level reasoning across any task.
Reactive Machines: Perform tasks without learning from past experiences.
Limited Memory: Use historical data to make decisions (common in modern ML).
Theory of Mind & Self‑Aware AI: More advanced, theoretical stages of AI that involve understanding emotions, awareness, and identity.
3. Algorithms, Data, and Training
Algorithms: Step‑by‑step rules computers follow to solve problems.
Datasets: Essential for training AI to recognize patterns.
Training: Feeding data to a model so it learns and improves.
Fine‑Tuning: Adapting a pretrained model to a specific task.
4. Machine Learning (ML)
Machine Learning: Enables systems to learn patterns from data automatically.
ML Categories
Supervised Learning: Model learns from labeled data.
Unsupervised Learning: Finds hidden patterns in unlabeled data (e.g., clustering).
Reinforcement Learning: Learns by trial and error using rewards and penalties.
5. Deep Learning & Neural Networks
Deep Learning: Uses multi‑layer neural networks to identify complex patterns.
Artificial Neural Networks (ANNs): Modeled after the brain with interconnected nodes.
GANs (Generative Adversarial Networks):
Generator: Produces new synthetic data.
Discriminator: Judges whether data is real or fake.
Deepfakes: Realistic but fake audio/video created via AI.
6. Generative AI & NLP
Generative AI: Creates new content (text, images, audio).
Large Language Models (LLMs): AI models trained on huge text datasets.
GPT: Stands for Generative Pre‑trained Transformer.
Transformer Models: Use attention mechanisms for understanding sequences.
NLP (Natural Language Processing): Helps computers understand human language.
Advantages & Limitations
Advantages: Efficient content automation.
Limitations: Requires large datasets; may hallucinate; may reflect training bias.
7. Robotics
Advantages: High precision, handles dangerous tasks, doesn’t tire.
Disadvantages: High cost, reduced human interaction, job displacement.
8. Internet of Things (IoT)
Benefits: Process optimization, component monitoring, smart home control.
Issues: Privacy, security vulnerabilities, energy consumption.
9. Blockchain & Other Emerging Technologies
Blockchain: Decentralized, secure ledger for transactions.
Quantum Computing: Uses quantum mechanics to solve complex problems.
Extended Reality (XR): Includes VR, AR, and Mixed Reality.
10. Ethics & Risks in AI
Misinformation: AI can produce convincing but false information.
Model Hallucinations: Mitigated by better data, prompt engineering, and external sources.
Black Box Problem: Hard to understand how AI makes decisions.
XAI (Explainable AI): Aims to increase transparency.
Web Scraping Ethics: Issues include violating terms of service and overloading servers.
Electricity Use: Large models require massive computational power.
Ethical Use: Requires disclosure of AI generation, fairness, and data protection.