MIS 301 • McCombs School of Business • UT Austin

IT Management Study Guide

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MIS 301 • Key Concepts

Vocabulary
Reference

Precise, citation-backed definitions drawn from lecture slides and course readings. Use the filters and search to study by chapter.

Graphical User Interface (GUI) Ch.SW

A visual interface that allows users to interact with software through graphical elements—icons, windows, drop-down menus, radio buttons, and check boxes—rather than typed text commands at a command line. Before GUIs, every computer user had to know command-line syntax. GUIs enabled non-programmers to use computers, democratizing computing in the workplace and at home. Every modern OS (Windows, macOS, iOS, Android) exposes a GUI to end users.

📖 Lecture Slides Ch.SW, p.8–9.

Software Ch.SW

A set of instructions that tells hardware what to do. Software comes in many categories depending on its function (OS, DBMS, middleware, enterprise application, consumer application), who can change its source code (open source vs. closed source), where the code executes (locally vs. hosted/SaaS), and what kind of standards it uses (open vs. closed). Understanding these four dimensions is the starting framework for classifying any software a manager encounters.

📖 Lecture Slides Ch.SW, p.2–4.

Operating System (OS) Ch.SW

The core software layer that acts as the interface between hardware and all users and applications on a computing device. Core functions: process keystrokes and mouse movements, send display signals, read and write disk files, control application processing, set look and feel, and manage/schedule the computer's resources. Every computing device has one—laptops, smartphones, video game consoles, microwave ovens, and car dashboards. Business models: sell the OS (Microsoft Windows), bundle with hardware (Apple macOS/iOS), or distribute freely (Linux, Android).

📖 Lecture Slides Ch.SW, p.11–14.

Database Management System (DBMS) Ch.SW

Software used for creating, maintaining, and manipulating data. A DBMS sits in the third layer of Konana's ecosystem (above the OS, below middleware). Most enterprise software operates in conjunction with a DBMS. A database application is a collection of forms, reports, queries, and application programs that process the underlying database. Multiple applications (order entry, purchasing, warehouse management) can share one database, eliminating data redundancy and improving quality. Major vendors: Oracle, Microsoft SQL Server, MySQL (open source), IBM DB2.

📖 Lecture Slides Ch.SW, p.16–22.

Middleware Ch.SW

Software that acts as "plumbing for data"—it sits between the DBMS and application layers in Konana's ecosystem, routing requests and enabling different applications and systems to communicate. In a web stack, a web server (e.g., Apache, Express.js, Node.js) is the middleware: it receives HTTP requests from the browser, coordinates with the DBMS, and delivers responses. In an enterprise context, middleware enables separate systems—patient records, billing, and lab results—to exchange data in real time without being rebuilt from scratch.

📖 Lecture Slides Ch.SW, p.24–26.

Enterprise Applications (ERP, CRM, SCM) Ch.SW

Software that addresses the needs of multiple users across an entire organization. ERP (Enterprise Resource Planning) integrates HR, manufacturing, inventory, purchasing, and order tracking into one system sharing a single database. SCM (Supply Chain Management) software coordinates supplier relationships and reduces the bullwhip effect. CRM (Customer Relationship Management) tracks customers across the full lifecycle and all channels, helping identify high- and low-value segments. A single unified database across these applications drives value chain efficiency and can make firms more attractive acquisition targets.

📖 Lecture Slides Ch.SW, p.27–32.

Data Quality & the Nestlé Example Ch.SW

The accuracy, completeness, and consistency of data stored in an organization's systems. Poor data quality is surprisingly common and costly. NestlĂ© sells 100,000 products in 200 countries. Of its 9 million vendor/customer/materials records, roughly half were obsolete or duplicated, and one-third of the remainder were inaccurate or incomplete—a vendor name abbreviated in one record but spelled out in another caused double-counting. After a SAP ERP overhaul consolidating everything into one database, NestlĂ© saved $30 million per year on vanilla alone from its American operations.

📖 Lecture Slides Ch.SW, p.33.

User vs. Enterprise Applications Ch.SW

User applications are used on a personal device and typically support tasks performed by a single user (e.g., Excel, Google Chrome, Angry Birds). Enterprise applications address the needs of multiple users throughout an organization or work group (e.g., SAP ERP, Salesforce CRM). Enterprise applications work in conjunction with a shared DBMS so that all departments access the same data, unlike user applications which typically operate on local files.

📖 Lecture Slides Ch.SW, p.34–35.

Moore's Law Ch.10

An empirical observation, first published by Gordon Moore (co-founder of Intel) in 1965, that the number of transistors on an integrated circuit roughly doubles approximately every 18–24 months, yielding exponential improvements in computing performance per dollar. It is not a physical law but became a business plan and expected pace of innovation for the semiconductor industry.

📖 Moore, G.E. (1965). "Cramming more components onto integrated circuits." Electronics, 38(8). | Lecture Slides Ch.10, p.5.

Transistor Ch.10

A semiconductor device that acts as an electronic switch, representing binary data by toggling between two states: on (= 1) and off (= 0). Modern computer chips contain billions of transistors packed together to perform complex computations.

📖 Gallaugher, J. (2023). Information Systems: A Manager's Guide to Harnessing Technology, Ch.6. | Lecture Slides Ch.10, p.10.

Bit (Binary Digit) Ch.10

The fundamental unit of digital information, taking a value of either 0 or 1. The term "bit" is a portmanteau of "binary digit." Computers represent all data—text, images, video, code—as sequences of bits. Data transfer speeds (internet, Wi-Fi) are measured in bits per second (bps, Mbps, Gbps). Note: lowercase "b" = bits; uppercase "B" = bytes.

📖 Shannon, C.E. (1948). "A mathematical theory of communication." Bell System Technical Journal. | Lecture Slides Ch.10, p.19.

Byte & Storage Units Ch.10

A byte = 8 bits ≈ one keyboard character. Storage is measured in Bytes (capital B): 1 KB ≈ 1,000 bytes (one typewritten page); 1 MB ≈ 1 million bytes (one MP3 ≈ 3 MB); 1 GB ≈ 1 billion bytes (one DVD ≈ 4.7 GB); 1 TB ≈ 1 trillion bytes (Library of Congress ≈ 20 TB); 1 PB ≈ 1 quadrillion bytes; 1 EB ≈ 1 sextillion bytes.

📖 Gallaugher (2023), Ch.6. | Lecture Slides Ch.10, p.12.

CPU (Central Processing Unit) Ch.10

The primary processor that executes instructions in a computer. Using the "data kitchen" analogy: the CPU is the chef that runs the computer by following software (its recipes). The CPU uses main memory (RAM) as its active workspace and stores completed work or future-needed data in long-term storage.

📖 Gallaugher (2023), Ch.6. | Lecture Slides Ch.10, p.9.

Price Elasticity of Demand (for Technology) Ch.10

An economic measure of how sensitively consumer demand responds to a change in price. Demand for computing technology is highly elastic—as prices fall, consumers find entirely new uses and demand far more. Example: storage prices fell from $399 for 5 GB (iPod, 2001) to free for 5 GB (iCloud, 2011), and total data storage consumed by consumers grew by orders of magnitude.

📖 Gallaugher (2023), Ch.6. | Lecture Slides Ch.10, p.6.

Multicore Processor Ch.10

A microprocessor containing two or more independent calculating cores on a single piece of silicon. A group of multicore chips typically outperforms a single fast chip on parallel workloads (tasks that can run simultaneously), while running cooler and drawing less power. Multicore processors can also run legacy software written for single-core chips by using only one core at a time.

📖 Gallaugher (2023), Ch.6. | Lecture Slides Ch.10, p.16.

GPU & ASICs Ch.10

A GPU (Graphics Processing Unit) is a chip originally designed for rendering computer graphics, requiring the simultaneous execution of thousands of smaller calculations (high parallelism). This massively parallel architecture turned out to be ideal for AI/ML training. The general category for purpose-built chips optimized for specific tasks is Application-Specific Integrated Circuits (ASICs). Nvidia's GPUs are the dominant ASIC for AI workloads.

📖 Gallaugher (2023), Ch.6. | Lecture Slides Ch.10, p.16.

E-Waste (Electronic Waste) Ch.10

Discarded, often obsolete electronic devices and components. Global e-waste reached 62 million tons in 2022 and is projected to rise to 74 million tons by 2030. E-waste contains toxic substances (lead, cadmium, mercury) that contaminate soil and water if not processed properly. Informal recycling by burning is common in developing countries because it is often cheaper to ship e-waste abroad than to recycle it responsibly. The U.S. has no comprehensive federal e-waste recycling law.

📖 Global E-waste Monitor 2024. | Gallaugher (2023), Ch.6. | Lecture Slides Ch.10, p.27–29.

Quantum Computing Ch.10

An emerging computing paradigm that uses quantum bits (qubits) instead of classical binary bits. Unlike a bit (strictly 0 or 1), a qubit can represent 0, 1, or both simultaneously through quantum superposition. Potential applications include predicting the weather months in advance, hyperdetailed human body simulations, and unbreakable cryptographic systems. Quantum computing is not yet commercially feasible.

📖 Preskill, J. (2018). "Quantum Computing in the NISQ Era and Beyond." Quantum, 2, 79. | Lecture Slides Ch.10, p.25.

Konana's Software Ecosystem Ch.10 & 15

A layered model of information technology infrastructure proposed by Prabhudev Konana (2007). From innermost to outermost: Hardware → Operating System → Database Management System → Middleware → Enterprise Applications → Consumer Applications. Because each layer depends on the layers beneath it, organizations face lock-in and switching costs when changing any layer, since changes cascade upward through the stack.

📖 Konana, P. (2007). Cited in Gallaugher (2023), Ch.6 & Ch.9. | Lecture Slides Ch.10 p.8; Ch.15 p.8.

Switching Costs & Lock-In Ch.10 & 15

The financial, operational, and psychological expenses incurred when changing from one technology product, vendor, or system to another. In Konana's ecosystem model, switching costs arise because each software layer depends on layers beneath it. In SaaS, switching costs create vendor lock-in: if a SaaS provider fails or raises prices, customers may face expensive, time-consuming migration to an alternative platform.

📖 Gallaugher (2023), Ch.6 & Ch.9. | Lecture Slides Ch.10 p.8; Ch.15 p.21.

Latency Ch.10 & 15

The delay between initiating a request and receiving a response. In cloud and SaaS computing, latency refers specifically to the time added by the round trip a data request must make between a user's device and a remote server over the internet. High latency can significantly degrade the performance of real-time applications. Online gaming requires low latency (under 50 ms); streaming 4K video tolerates higher latency because video buffers ahead.

📖 Gallaugher (2023), Ch.6 & Ch.9. | Lecture Slides Ch.10 p.18–20; Ch.15 p.21–25.

Bandwidth Ch.10 & 15

The maximum rate at which data can be transmitted over a network connection, measured in bits per second (Mbps or Gbps). ISPs advertise bandwidth in Megabits (Mbps); file sizes are in Megabytes (MB). Divide Mbps by 8 to get MB/s download speed. Bandwidth is analogous to highway lanes; latency is the speed limit—both matter for network performance.

📖 Gallaugher (2023), Ch.6 & Ch.9. | Lecture Slides Ch.10 p.19–20.

SaaS (Software as a Service) Ch.15

A software delivery model in which applications are hosted on a vendor's remote servers and accessed by users through a web browser over the internet, rather than installed locally. In SaaS, the vendor manages all infrastructure layers. Examples: Google Sheets, Salesforce CRM, Office 365, Canvas. Business model: typically monthly subscription or usage-based pricing.

📖 Gallaugher (2023), Ch.9. | NIST SP 800-145 (2011). | Lecture Slides Ch.15, p.9, 13.

IaaS (Infrastructure as a Service) Ch.15

A cloud computing model in which a third-party provider owns and manages physical hardware (servers, storage, networking), while the customer manages the operating system, databases, middleware, and all applications running on that hardware. Example: Netflix and Walmart run their operations on Amazon Web Services (AWS)—they manage their own software stack on Amazon's physical hardware.

📖 Gallaugher (2023), Ch.9. | NIST SP 800-145. | Lecture Slides Ch.15, p.9.

Total Cost of Ownership (TCO) Ch.15

A comprehensive accounting of all costs associated with acquiring and operating a technology system over its entire lifecycle. The purchase price represents only approximately 20% of TCO; the remaining ~80% consists of hidden costs including: requirements analysis and site prep, implementation and deployment, training, initial efficiency loss, ongoing operational support, maintenance, and strategic development to keep up with a changing competitive landscape.

📖 Gallaugher (2023), Ch.9. | Gartner Research on IT TCO. | Lecture Slides Ch.15, p.17–18.

Freemium Pricing Ch.15

A pricing strategy in which a basic version of a product or service is offered at no cost to attract users, while advanced features, higher usage limits, or a premium version are available for a fee. Common among SaaS providers as a customer acquisition strategy. Examples: Spotify (free with ads vs. paid), Slack (free tier vs. paid plans), Dropbox (free storage vs. paid expansion).

📖 Anderson, C. (2009). Free: The Future of a Radical Price. | Gallaugher (2023), Ch.9. | Lecture Slides Ch.15, p.13.

Open vs. Closed Standards Ch.15

Open standards are publicly available technical specifications that allow any company to create compatible or interoperable software without requiring permission from the original developer (e.g., Microsoft Windows—third parties can build Windows-compatible software freely). Closed standards are controlled by the owning firm, requiring its explicit permission before third parties may develop complementary applications (e.g., Apple's iOS App Store—developers must comply with Apple's approval process).

📖 Gallaugher (2023), Ch.8. | Lecture Slides Ch.15, p.4.

Software Piracy Ch.15

The unauthorized copying, distribution, or use of proprietary software in violation of its license agreement. SaaS dramatically reduces piracy risk compared to traditional installed software because the application runs on the vendor's server and is never installed on the user's device—there is no executable file to copy or share illegally. Users must authenticate via the internet to access the service.

📖 BSA. Global Software Survey. | Gallaugher (2023), Ch.9. | Lecture Slides Ch.15, p.14.

Source Code Ch.8

The human-readable set of instructions written by a programmer in a specific programming language (e.g., Python, Java, C++) that defines how software behaves. Source code must be either compiled (translated entirely into machine code before execution) or interpreted (translated line-by-line at runtime). Whether source code is publicly shared or kept secret is the defining difference between open source and closed source software.

📖 Gallaugher (2023), Ch.8. | Lecture Slides Ch.8 (OSS), p.9–10.

GNU GPL & Free Software Foundation (FSF) Ch.8

The Free Software Foundation (FSF), founded in 1983 by Richard Stallman, holds that restricting access to software source code is morally wrong. It created the GNU General Public License (GPL)—a "copyleft" license guaranteeing users the right to run, study, modify, and redistribute software. The GPL requires that any derivative work built on GPL-licensed code must itself be released under the GPL. It is the legal foundation that allowed open source infrastructure to spread freely.

📖 Free Software Foundation. GNU General Public License v3. | Lecture Slides Ch.8 (OSS), p.15.

Linux & the Linux Kernel Ch.8

A free, open-source, Unix-like operating system kernel (the core of an OS that manages CPU, memory, and device I/O) created in 1991 by Linus Torvalds. Linux powers the majority of the global internet infrastructure, most cloud servers (including much of Microsoft Azure), and is the basis for Android (the world's most-used mobile OS). Its mascot is Tux the penguin.

📖 Torvalds, L. (1991). Original Linux kernel announcement. | Linux Foundation. | Lecture Slides Ch.8 (OSS), p.14.

Linux Foundation & the "Bus Factor" Ch.8

By the early 2000s, the global internet ran on Linux maintained by a small group of unpaid volunteers—a dangerous "bus factor" (if key maintainers were hit by a bus, development would collapse). Rivals also feared fragmentation reminiscent of the "Unix Wars" (1980s–90s). To address both risks, IBM, HP, Intel, and Oracle formed the Linux Foundation (2007)—a neutral industry trade association that funds core maintainers, standardizes the code, and legally protects the Linux trademark.

📖 The Linux Foundation. linuxfoundation.org. | Gallaugher (2023), Ch.8. | Lecture Slides Ch.8 (OSS), p.16–17.

Technology Stack (Tech Stack) Ch.8

A coordinated set of layered software technologies that work together to make a website or application function. Each layer in the stack handles a different concern—the OS manages hardware resources, the database handles data persistence, the web server (middleware) routes requests, and the programming language/framework builds the user-facing application. Stacks are how Konana's ecosystem model maps to real-world products. Developers interact between layers via APIs (Application Programming Interfaces).

📖 Gallaugher (2023), Ch.8. | Lecture Slides Ch.8 (OSS), p.21.

LAMP Stack Ch.8

The original open-source web application stack, still powering 40%+ of websites. The acronym stands for: Linux (OS), Apache (web server / middleware), MySQL (relational database), PHP/Python/Perl (programming languages). In Konana's ecosystem: Linux = OS layer; MySQL = DBMS layer; Apache = Middleware layer; PHP/Python = Application layer. Powers Facebook (originally), Wikipedia, YouTube (originally), and Slack.

📖 Gallaugher (2023), Ch.8. | Lecture Slides Ch.8 (OSS), p.23 & p.25.

MEAN Stack Ch.8

A modern open-source web stack using JavaScript across all layers: MongoDB (NoSQL/document database), Express.js (web server framework / middleware), Angular (front-end JavaScript framework), Node.js (server-side JavaScript runtime). Key advantages over LAMP: (1) all layers use a single language (JavaScript), making it easier to hire "full-stack" developers; (2) MongoDB's flexible document model is better for highly dynamic real-time applications (e.g., Netflix, Uber) where data structures change frequently.

📖 Gallaugher (2023), Ch.8. | Lecture Slides Ch.8 (OSS), p.24 & p.26.

OSS Business Model Ch.8

Open source software vendors do not sell source code (it is free). Instead they monetize surrounding services. The four main revenue streams are: (1) Support & Stability—enterprises pay for guaranteed professional support; (2) Security & Compliance—selling certified, hardened versions for regulated industries; (3) Premium Tools for Scale ("The Anaconda Model")—selling enterprise-grade management tools on top of the free software; (4) Hosted Managed Services—running the software for customers in the cloud.

📖 Gallaugher (2023), Ch.8. | Lecture Slides Ch.8 (OSS), p.12 & p.30.

Project Management Triple Constraint Ch.17

A foundational project management model stating that every project is governed by three interdependent drivers—Scope (requirements/features), Resources (money, people, equipment), and Schedule (time)—and that adjusting any one dimension requires a trade-off against the other two. Example: adding scope without increasing resources will extend the schedule; compressing the schedule without reducing scope requires more resources.

📖 Gallaugher (2023), Ch.11. | PMI PMBOK Guide. | Lecture Slides Ch.17, p.4.

Brook's Law & Diseconomies of Scale Ch.17

Brook's Law (from Fred Brooks' 1975 book The Mythical Man-Month): "Adding manpower to a late software project makes it later." New team members require onboarding time, existing members must mentor them, and communication overhead grows non-linearly with team size. This is called diseconomies of scale: as development teams grow, average contribution per worker decreases—the opposite of economies of scale.

📖 Brooks, F. (1975). The Mythical Man-Month. | Gallaugher (2023), Ch.11. | Lecture Slides Ch.17, p.3.

Waterfall Method Ch.17

A relatively linear, sequential approach to software development in which each phase (requirements → design → development → testing → deployment) must be completed and approved before the next begins. Benefits include surfacing all requirements up front and creating a clear blueprint. Drawbacks: very rigid, slow to implement, requires precisely known requirements from the start, and cannot easily accommodate changes mid-project. Works for civil engineering; rarely works for software.

📖 Royce, W.W. (1970). Original waterfall model paper. | Gallaugher (2023), Ch.11. | Lecture Slides Ch.17, p.11.

Agile Method Ch.17

The dominant modern software development methodology. Agile develops work continually and iteratively, breaking larger projects into smaller components delivered in short cycles (sprints). Goal: more frequent product rollouts and constant improvement. The cyclic process: Plan → Design → Develop → Test → Deploy → Review → (repeat). Popular due to speed and flexibility. "Agile sounds chaotic, but products actually ship."

📖 Beck, K. et al. (2001). Manifesto for Agile Software Development. | Gallaugher (2023), Ch.11. | Lecture Slides Ch.17, p.12–13.

Scope Creep Ch.17

The gradual, often uncontrolled expansion of a project's requirements during development, beyond what was originally agreed upon. Each individual addition may seem small, but cumulative scope creep is one of the leading causes of technology project failure—directly driving budget overruns, schedule delays, and team burnout. Listed explicitly in the slides as a primary failure mode, alongside poor goal setting, weak leadership, inadequate resources, and poor communication.

📖 Gallaugher (2023), Ch.11. | Lecture Slides Ch.17, p.19.

Low Code / No Code (LCNC) Ch.17

Highly visual software development tools that allow users—called citizen developers—to create information systems with little or no traditional coding. The LCNC market was ~$27 billion in 2023, growing 20% year-over-year. Major providers: Google (AppSheet), Microsoft (Power Apps), Oracle (APEX), Salesforce. Risks of poorly governed LCNC deployments include: inconsistent/duplicate data, regulatory violations (HIPAA/FERPA/GDPR), vendor abandonment, and security vulnerabilities.

📖 Gallaugher (2023), Ch.11. | Gartner Low-Code Market Report (2023). | Lecture Slides Ch.17, p.17–18.

Software Foundations • MIS 301 Quiz

Software for
Managers

5 scenario-based questions covering Konana's ecosystem, operating systems, DBMSs, middleware, enterprise applications, and data quality.

📖 Topics covered: Classifying software (source, location, standards) · Konana's Ecosystem layers · Operating System functions · DBMS & database applications · Middleware · Enterprise software (ERP/CRM/SCM) · Total Cost of Ownership · Data quality
Q1 Classifying Software — The Four Dimensions
A MIS 301 professor holds up a laptop and points to four software products: (1) Microsoft Excel installed on the machine; (2) Excel accessed through Office 365 in a browser; (3) LibreOffice Calc installed on the machine; and (4) Apple Numbers installed on a Mac. She asks students to classify each product using the four software dimensions from the slides.
According to the Software Examples table from class, which product is correctly classified as Open Source / Local / Open Standards?
✔ Correct: D — Explanation From the slides' Software Examples table: LibreOffice is the only product in the list classified as Open Source / Local / Open Standards. Microsoft Excel (desktop) is Closed Source / Local / Open Standards. Excel in Office 365 is Closed Source / Hosted (SaaS) / Open Standards. Apple Numbers is Closed Source / Local / Closed Standards — Apple requires developer permission to build compatible apps in its ecosystem. A is wrong—Excel's source code is proprietary. B is wrong—Microsoft does not publish Office's source code. C is wrong—Apple Numbers uses closed standards; developers need Apple's explicit approval to integrate with its ecosystem.
Q2 Konana's Ecosystem — Identifying Layers
A startup's CTO sketches their technology stack on a whiteboard: at the center is bare-metal server hardware. Above that sits Ubuntu Linux. Above that is MySQL, which stores all user data. Above that is Apache, which routes incoming HTTP requests between the browser and the application. At the outermost layer is their custom-built Python/Flask customer-facing web app. Her co-founder asks her to label each component using Konana's Software Ecosystem model from class.
Which labeling of the five components is CORRECT according to Konana's model?
✔ Correct: C — Explanation Konana's ecosystem layers from innermost to outermost: Hardware → Operating System → Database Management System → Middleware → Enterprise/Consumer Applications. Ubuntu Linux is a Linux distribution (Operating System). MySQL is a relational database management system (DBMS layer). Apache is a web server that routes requests between the browser and the application—it is the Middleware layer (data plumbing). The Python/Flask web app is the Consumer or Enterprise Application layer. A, B, D all scramble these roles—most commonly confusing MySQL (a database) with middleware, or Apache (a web server) with the OS or DBMS.
Q3 DBMS & Database Applications — Shared Data Advantage
A mid-size retailer has three separate databases: one for its e-commerce order entry system, one for its warehouse management system, and one for its purchasing team. When a customer places an order online, warehouse staff have no real-time visibility into available inventory, and the purchasing team independently orders stock the warehouse already has. The CIO proposes replacing the three siloed databases with a single shared DBMS and connecting all three applications to it.
Which outcome MOST directly explains why the CIO's proposal would improve the firm's operations, according to the database application model from class?
✔ Correct: B — Explanation The slides explicitly state: "A firm's database management system can be set up to work with several applications both within and outside the firm. 1 database = increased value chain efficiency = more $$." Multiple applications (order entry, warehouse management, purchasing) can have different purposes and features but all process the same data stored in a common database. This eliminates the data silos causing the retailer's inventory visibility and double-purchasing problems. A is wrong—middleware (web servers, integration layers) is still needed to route requests between applications and the DBMS; a shared database doesn't eliminate middleware. C is wrong—database architecture has no bearing on whether application source code is open or closed. D is wrong—the OS layer is always present in Konana's ecosystem; no database change removes it.
Q4 Middleware — The "Plumbing" Role
A regional hospital uses three separate software systems: one for patient records (built in 2008), one for billing (built in 2014), and a brand-new lab results portal. A patient's doctor needs to view lab results in the patient records system without staff manually re-entering data. The hospital's IT director says they don't need to replace any of the three systems—instead, they can add a fourth component that will allow the existing systems to exchange data automatically in real time.
What layer of Konana's ecosystem is the IT director describing, and what is its core function?
✔ Correct: C — Explanation The slides describe middleware as "plumbing for data"—software that sits between the DBMS and applications in Konana's ecosystem, routing requests and enabling different applications to communicate. The hospital scenario matches the Instapoll #4 scenario from class: separate applications for patient records, billing, and lab results that "automatically exchange data in real time" through a component enabling their integration. That component is middleware. A is wrong—the OS manages hardware resources; it does not route data between application-layer systems. B is wrong—a DBMS centralizes data storage, but the scenario describes three separately-built applications with their own existing data stores; middleware bridges them without a full database migration. D is wrong—a new consumer application (a front-end portal) could display data, but the IT director specifically says no system needs to be replaced; the solution is an integration layer, not a new application layer on top.
Q5 Data Quality & ERP — The NestlĂ© Lesson
A global consumer goods company discovers that its procurement team across 40 countries has been independently negotiating contracts with many of the same suppliers—sometimes under slightly different vendor names or entity IDs in each region's local system. One supplier appears as "BASF Chemical AG," "BASF-Chem," and "BASF AG" across three databases. As a result, the company has no accurate picture of how much it spends with BASF globally and cannot negotiate volume discounts. The CFO asks what caused this problem and what the solution is.
Which diagnosis and solution MOST directly reflects what the slides teach through the Nestlé case?
✔ Correct: D — Explanation The NestlĂ© case directly illustrates this scenario. NestlĂ© had 9 million vendor/customer/materials records of which roughly half were obsolete or duplicated, and one-third were inaccurate—a vendor name abbreviated in one record but spelled out in another led to double-counting. The solution was a SAP ERP overhaul that consolidated everything into ONE database, enabling accurate global spend analysis. The result: $30M in annual savings on vanilla alone from U.S. operations. The slides teach: "1 database = increased value chain efficiency = more $$." A is wrong—the problem is architectural (siloed systems), not a deficiency of open source databases; Oracle and SQL Server can also produce duplicate records if deployed in silos. B is wrong—scope creep is a project management failure mode, not a data quality issue caused by multiple databases. C is wrong—latency is a network/cloud performance issue; it doesn't cause duplicate vendor records across independent systems.

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Chapter 8 • MIS 301 Quiz

Open Source
Software (OSS)

5 scenario-based questions targeting application and analysis. Select the best answer to check your understanding.

📖 Topics covered: Open vs. closed source · OSS business model · Linux & the Linux Foundation · LAMP vs. MEAN stacks · OSS strategic value for firms
Q1OSS Business Model — How Vendors Make Money
A hospital's IT director is considering switching from a $120,000/year proprietary database to MySQL, an open source database that can be downloaded free of charge. A vendor rep from MySQL's parent company (Oracle) follows up and says: "We'd love to help you make that switch. You get the database for free, but we'd like to talk about our enterprise support contract." The director is confused—if the software is free, why would the hospital pay Oracle anything?
Which statement BEST explains how open source software vendors like Oracle (MySQL) generate revenue when the software itself is free?
✔ Correct: C — Explanation The OSS business model does not sell source code—it sells the support, expertise, and stability that enterprises need around the free software. Revenue streams include: guaranteed professional support contracts, security-certified/hardened software editions, premium enterprise management tools, and hosted managed services. A is wrong—access to OSS source code is free and unrestricted. B is wrong—advertising is a consumer SaaS model. D is wrong—per-user royalties are a closed-source licensing model.
Q2Linux Foundation — Why Rivals Cooperated
By 2003, the global internet ran almost entirely on Linux servers. Billions of dollars of corporate infrastructure depended on software maintained by a small group of volunteer programmers. Technology executives at IBM, HP, Intel, and Oracle started losing sleep over this. They were also haunted by the memory of the 1980s–90s "Unix Wars," when competing proprietary versions of Unix fragmented the market and left everyone worse off.
Which TWO risks MOST directly drove competing companies to set aside their rivalry and collectively fund the Linux Foundation?
✔ Correct: B — Explanation Two specific risks drove the Linux Foundation's formation: the "bus factor" (unpaid volunteers could stop maintaining critical global infrastructure at any time) and fragmentation risk (fear of a repeat of the Unix Wars). The solution was a neutral, jointly funded trade association (the Linux Foundation, 2007). A is wrong—the GPL does not expire. C is wrong—the GPL explicitly permits commercial use. D is wrong—Linux has never required purchase.
Q3LAMP Stack — Components & Konana's Ecosystem
A startup is building a social media app. The founding engineer announces: "We'll use the classic open-source web stack." She writes four technologies on the whiteboard: Linux, Apache, MySQL, and PHP. Her co-founder, fresh from MIS 301, immediately maps each one to a layer of Konana's software ecosystem.
Which mapping of LAMP components to Konana's ecosystem layers is CORRECT?
✔ Correct: D — Explanation In Konana's ecosystem: Linux is the OS; MySQL is the DBMS; Apache is the Middleware web server (routes HTTP requests between layers); PHP/Python/Perl builds the Consumer or Enterprise Application layer. The most common error is confusing Apache (a web server = middleware) with the OS, or MySQL (a database) with middleware.
Q4LAMP vs. MEAN — Choosing the Right Stack
Team Alpha is building a content-heavy blog platform. Their engineers know several programming languages (PHP, Python, Ruby), and their data has a consistent, predictable structure. Team Beta is building a real-time ride-sharing app where data (driver locations, surge pricing, trip status) changes constantly, and they want to hire developers who only need to know one language from front-end to back-end.
Based on the characteristics of LAMP and MEAN stacks, which stack recommendation for each team is MOST appropriate?
✔ Correct: B — Explanation LAMP is the classic stack with a relational MySQL database (ideal for structured, consistent data like blog posts) and supports multiple programming languages—a good fit for Team Alpha. MEAN was built specifically for highly dynamic real-time applications (like Netflix and Uber) where data changes constantly. MEAN's key hiring advantage: all layers use JavaScript, making it easier to find full-stack developers.
Q5OSS Strategic Value — Competitive Advantage & Fixed Costs
Company A spends $8M per year building and maintaining its own proprietary OS, web server, and database from scratch. Company B adopts the open-source LAMP stack, paying only $400,000 per year in support contracts, and redirects the $7.6M in savings into AI-powered product recommendations and a personalized loyalty program. Three years later, Company B has significantly higher customer retention and revenue growth.
Which insight from the OSS slides BEST explains why Company B's approach created a competitive advantage while Company A's did not?
✔ Correct: C — Explanation The key insight from class: "Keeping the lights on does not create competitive advantage." Running commodity infrastructure (OS, web server, database) is a necessity, not a differentiator. OSS frees funds that firms would otherwise spend on these fixed infrastructure costs. Company B redirected $7.6M from a non-differentiating fixed cost to genuinely differentiating innovations (AI recommendations, loyalty program).

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Chapter 10 • MIS 301 Quiz

Moore's Law
& Hardware

5 scenario-based questions targeting application and analysis. Select the best answer to check your understanding.

📖 Topics covered: Moore's Law · Price elasticity of technology demand · Bits vs. bytes · GPU/ASICs for AI · E-waste challenges
Q1Moore's Law — Nature & Origin
A business professor tells her class: "What we call 'Moore's Law' sounds like it was discovered by physicists in a laboratory, but it actually started as an observation published in a 1965 industry paper. The semiconductor industry later adopted this observation as a planning target." A student asks whether chip performance is guaranteed to keep doubling indefinitely.
Which statement BEST characterizes Moore's Law and why chip performance cannot be guaranteed to keep improving at this historical rate?
✔ Correct: B — Explanation Gordon Moore, co-founder of Intel, published his observation in 1965 that transistor counts on chips roughly doubled at regular intervals. This was an empirical finding—not a physical law—that the semiconductor industry voluntarily adopted as its innovation roadmap. Today, transistor miniaturization is approaching the limits of physics, which is why the doubling cadence has slowed.
Q2Price Elasticity of Demand for Technology
In 2001, Apple released the first iPod with 5 GB of storage for $399. By 2011, Apple offered 5 GB of iCloud storage free of charge. During that decade, consumers went from storing a few hundred songs to expecting entire photo libraries, 4K videos, and automatic device backups to live permanently in the cloud. A MIS professor attributes this dramatic behavioral shift to a core economics principle.
Which concept BEST explains why the dramatic drop in storage costs led to a dramatic increase in storage demand?
✔ Correct: D — Explanation Price elasticity of demand measures how sensitively quantity demanded responds to price changes. Demand for computing technology is highly elastic: as storage prices plummeted from $399 for 5 GB to free, consumers didn't just buy the same amount more cheaply—they invented new behaviors that consumed far more. Managers are often blindsided by how dramatically cheap tech reshapes consumer behavior.
Q3Bits vs. Bytes — ISP Speed Gotcha
A student signs up for a campus internet plan advertised as "500 Mbps." Excited to download a large design file, she watches the download bar and sees the file arriving at roughly 62 MB/s. She tells her roommate: "My connection says 500, but it's only downloading at 62—something must be broken." Her roommate, who just finished the MIS 301 hardware module, laughs and explains the math.
Which explanation BEST clarifies why a 500 Mbps connection produces approximately 62 MB/s of download speed?
✔ Correct: C — Explanation The golden rule: 8 bits = 1 byte. ISPs advertise bandwidth in Megabits per second (Mbps) while file sizes are displayed in Megabytes (MB). To convert: 500 Mbps Ă· 8 = 62.5 MB/s—exactly what the student observes. Lowercase "b" = bits (network speed), uppercase "B" = Bytes (storage).
Q4GPU / ASICs for AI — Purpose-Built Chips
An AI research lab is purchasing hardware to train large language models. The lab director says: "We should buy Nvidia chips rather than standard Intel CPUs. Nvidia's chips were originally designed to render video game graphics—a task that requires processing thousands of smaller calculations simultaneously. That same massively parallel architecture turned out to be exactly what AI model training needs."
What type of chip is the director recommending, and what is the general category term for purpose-built chips like it?
✔ Correct: B — Explanation GPUs (Graphics Processing Units) were designed by Nvidia for rendering graphics, requiring thousands of small matrix calculations simultaneously. This massively parallel architecture proved ideal for AI/ML training. The broader term for chips designed for specific tasks rather than general-purpose computation is Application-Specific Integrated Circuits (ASICs). "PEUs" is not a real classification; quantum and neuromorphic chips are distinct emerging technologies.
Q5E-Waste — Challenges & Root Causes
A student writing a sustainability report discovers that global e-waste reached 62 million tons in 2022 and is projected to hit 74 million tons by 2030. Despite growing awareness, informal e-waste processing—including burning electronics in open air, which exposes workers to lead, cadmium, and mercury—continues in many developing countries. She also notes that the United States has no comprehensive federal law requiring proper e-waste recycling.
Which factor MOST directly explains why proper e-waste recycling remains uncommon globally despite the known environmental and health harms?
✔ Correct: D — Explanation Responsible e-waste recycling is expensive. Shipping electronics abroad where regulations are weaker and informal burning is tolerated is often the cheaper path. The U.S. lacks a comprehensive federal e-waste recycling law, making enforcement inconsistent. Electronics contain valuable recoverable materials (gold, copper, rare earth metals)—informal burning destroys value and releases toxins. Robotics have not fully solved the problem at global scale.

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Chapter 15 • MIS 301 Quiz

Software as a
Service (SaaS)

5 scenario-based questions targeting application and analysis. Select the best answer to check your understanding.

📖 Topics covered: Open vs. closed source & standards · SaaS / IaaS / PaaS · Total Cost of Ownership (TCO) · SaaS piracy resistance · SaaS risks (vendor dependence, latency)
Q1Open Source & Closed Standards
A student club treasurer uses LibreOffice Calc for the club's budget. A programmer downloads LibreOffice's publicly available source code and customizes it to integrate directly with the club's payment processor. Meanwhile, the treasurer's friend uses Apple Numbers and notes that Apple does not publish Numbers' source code, and third-party developers must get Apple's explicit permission to build apps that integrate with Apple's software ecosystem.
Which row CORRECTLY classifies BOTH tools across the source code and standards dimensions from class?
✔ Correct: B — Explanation LibreOffice is open source (anyone can download and modify the code) and uses open standards (other developers can create compatible files or integrations without permission). Apple Numbers is closed source (Apple does not publish its code) and uses closed standards (developers need Apple's approval to build integrating apps). A is wrong—LibreOffice uses open, not closed, standards. C is wrong—LibreOffice's source code is publicly available. D is wrong—Apple Numbers is closed source.
Q2SaaS vs. IaaS vs. PaaS
Company A (UT Austin) pays Microsoft a monthly subscription for Office 365—Microsoft manages everything: physical servers, the OS, the database, and the Office applications themselves. Company B (Netflix) rents physical servers from Amazon Web Services but installs and manages its own OS, database, and streaming software on those servers. Company C's enterprise customers (Salesforce clients) rent all infrastructure layers from a cloud provider but build and manage only their own custom CRM applications on top of Salesforce's platform.
Which assignment of cloud service models is CORRECT for all three companies?
✔ Correct: C — Explanation SaaS: the vendor manages everything including the application (UT/Office 365). IaaS: the vendor provides physical hardware only; the customer manages OS, database, and apps (Netflix on AWS). PaaS: the vendor manages all infrastructure layers; the customer manages only their own application (Salesforce's enterprise clients).
Q3Total Cost of Ownership (TCO)
A regional hospital's CFO reviews a $400,000 quote for a new on-premise patient records system. She says: "That's 40% of our annual IT budget—we can't afford it." The CIO pushes back: "The $400,000 is only a fraction of what this system will truly cost us. You haven't accounted for consultant fees to deploy it, six months of reduced staff productivity during the learning curve, the annual technical support contract, hardware refresh every four years, or adapting the system as healthcare regulations change."
What concept does the CIO's argument illustrate, and approximately what share of total system cost does the sticker price typically represent?
✔ Correct: B — Explanation Total Cost of Ownership (TCO) is the comprehensive accounting of all costs over a system's lifecycle. The initial purchase price represents roughly 20% of TCO; the remaining ~80% consists of hidden costs: requirements analysis, implementation, training, initial productivity loss, ongoing operational support, maintenance, and strategic adaptation costs. The iceberg analogy applies—most of the cost is beneath the surface.
Q4Why SaaS Reduces Software Piracy
A software developer sold her video-editing program as a downloadable desktop application for $199 per license. She constantly fought piracy: users would buy one license and share the installer file with dozens of friends. Frustrated, she redesigns the product entirely as a SaaS application. Now users pay $15/month, log in through a web browser, and all processing happens on her servers—nothing is installed on the user's computer. The piracy problem essentially disappears overnight.
Why does the SaaS delivery model drastically reduce software piracy compared to the traditional downloaded-installer model?
✔ Correct: C — Explanation Traditional software piracy involves copying an installer or executable file. In a SaaS model, no software is installed on the user's device—the application runs entirely on the vendor's servers and users access it through a browser session. There is nothing to copy or share. Users must authenticate over the internet with valid credentials.
Q5SaaS Risks — Vendor Dependence & Latency
A finance manager is evaluating whether to move her 200-person firm from locally installed Excel to online Excel (Office 365 SaaS). Her IT colleague raises several concerns: the team will be dependent on Microsoft's uptime; if Microsoft discontinues the service or raises prices significantly, migrating thousands of files and retraining staff will be time-consuming and costly; and every time someone opens or saves a file, that action must travel from the user's laptop to Microsoft's data center and back before completing.
Which SaaS risk is the IT colleague describing when he highlights the delay caused by file operations traveling to Microsoft's remote data center?
✔ Correct: D — Explanation Latency is specifically the delay caused by a request traveling from a user's device to a remote server and back. In SaaS, every file operation involves this internet round trip. The class example with online Excel illustrated exactly this: computation happens on Microsoft's server, but the file travels through multiple network hops and "with this much network travel, latency can become a significant issue." Switching costs (A) refer to the expense of changing vendors, not per-operation delay.

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Chapter 17 • MIS 301 Quiz

Software Project
Management

5 scenario-based questions targeting application and analysis. Select the best answer to check your understanding.

📖 Topics covered: Systems development challenges · Project Management Triple Constraint · Brook's Law & diseconomies of scale · Waterfall vs. Agile methodology · Scope creep & why projects fail · Prototypes & wireframes · Low code / no code (LCNC)
Q1Brook's Law — Adding People to a Late Project
A software project at a mid-size logistics company is six weeks behind schedule. The VP of Engineering proposes: "Let's hire 12 new contract developers and throw them at the problem—more hands, faster finish." The project manager pushes back: "Adding people right now will actually make us later, not earlier."
Which concept does the project manager's warning illustrate, and why does adding people to a late software project make it later?
✔ Correct: C — Explanation Brook's Law, from Fred Brooks' The Mythical Man-Month (1975), states that adding people to a late software project makes it later. This happens because of diseconomies of scale: new developers require onboarding time, experienced members must pause to train newcomers, and communication overhead grows non-linearly. The net effect is that the project loses more capacity to coordination than it gains from new hires.
Q2Waterfall vs. Agile — Choosing the Right Methodology
Organization A is a city government building a new bridge inspection records system. The requirements are legally mandated and cannot change—every data field, workflow, and report format is defined in regulatory documents before a single line of code is written. Organization B is a startup building a consumer social app. They have a rough idea of core features but expect to learn from user feedback and pivot frequently based on what their early users actually do.
Based on their contexts, which development methodology is MOST appropriate for each organization?
✔ Correct: C — Explanation Waterfall's core benefit—surfacing all requirements up front—is most valuable when requirements are genuinely stable and well-defined (like legally mandated government systems). Agile's iterative, sprint-based approach is purpose-built for environments where requirements evolve rapidly and frequent delivery is valuable, like Organization B's consumer startup. B is wrong—Waterfall does work for projects with fully stable requirements. D is wrong—Waterfall is not universally government-mandated, and Agile is not inherently more expensive.
Q3Scope Creep — Why Projects Overrun
A regional bank is building a new customer portal. The original plan calls for account balance viewing, transaction history, and bill pay—to be delivered in 9 months for $1.2M. Three months in, the marketing team asks to add personalized product recommendations. Two weeks later, the compliance team requests an audit trail feature. The following month, the CEO asks for a budgeting tool after seeing a competitor's app. The project manager's schedule now shows 17 months and $2.8M.
Which failure mode from the slides MOST directly explains why the bank's project has more than doubled in cost and timeline?
✔ Correct: B — Explanation Scope creep is the gradual, often uncontrolled expansion of project requirements during development. No single addition seems catastrophic—a recommendation engine, an audit log, a budgeting widget—but together they add 8 extra months and $1.6M. This is the textbook definition of scope creep and is listed in the slides as one of the primary causes of technology project failure. Each stakeholder acted with good intentions, but without formal scope management, every "small" addition compounds.
Q4Prototypes & Wireframes — Value in Requirements Discovery
A hospital is replacing its nurse scheduling system. Business analysts interview nursing staff for two weeks and write a 60-page requirements document. Development begins, and six months later the team demos a working system. The nurses immediately identify a dozen critical problems: the shift-swap interface doesn't match their mental model, key summary data is buried three clicks deep, and emergency override workflows are counterintuitive. The project manager says: "We could have caught all of this on day one."
Which tool or technique, emphasized in the slides, would MOST effectively have prevented the expensive late-stage discovery of these usability problems?
✔ Correct: D — Explanation Prototypes and wireframes are specifically designed to solve this problem. As the slides note, they help users evaluate requirements by showing actual data in context, providing an opportunity for users to test interfaces, and serving as a communication device between users and developers. The 60-page requirements document described abstract functionality but couldn't convey what the interface actually felt like to use—prototypes would have let nurses interact with a mock-up months before expensive code was written.
Q5LCNC Risks — Governance & the HealthCare.gov Lesson
A regional insurance company's marketing operations director discovers Microsoft Power Apps and, without involving IT, builds 14 separate apps over 6 months for different team functions. Each app collects slightly different customer fields in different formats. No data validation rules are consistent across apps. Several apps store sensitive policyholder information in ways that may violate state insurance regulations. The IT director learns of this only when a regulatory audit flags it.
Which concern from the slides about low code / no code tools does this scenario MOST directly illustrate?
✔ Correct: C — Explanation The slides explicitly list the risks of poorly designed or governed LCNC systems: inconsistent or duplicate data (different customer fields across 14 apps), legal and regulatory violations (insurance regulation concerns), and security risks. The root cause: "Systems development goes beyond just creating an app. IT professionals bring specialized skills and enforce governance principles." A is wrong—the scenario's issues are about improper data handling and compliance, not inherent platform encryption failures. B is wrong—Brook's Law is about adding people to a late project. D is wrong—cost is not mentioned; LCNC tools are often cheaper short-term.

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