AFM 241 - Final Exam (W6-W12)

W6: Define **Analytics**

resources that help generate customer insights, identify growth opportunities, and stimulate innovations, producing competitive advantage

W6: **Early (or first)** advantage/ability

the ability to capture critical data assets can be difference between a dominating firm and an also-ran

W6: **Differentiation** (competitive advantage)

(be better, by being different), key in dsitinguishing operationally effective data from those efforts that can yield true strategic position

W6: Define **Databas**e (data organization)

single table or a collection of related tables

W6: Define **Database management systems (DMBS)** (data organization)

Software for creating, maintaining and manipulating data (aka database software)

W6: Define **structured query language (SQL)** (data organization)

a language used to create and manipulate databases

W6: Define **Business Intelligence**

combining aspects of reporting data exploration and ad hoc queries and sophisticated data modelling and analysis

* infrastructure for collecting, storing and analysis data the business produced
* databases, data warehouses, data marts fall under BI

W6: Define **Data Analytics**

tools and techniques for analyzing data (OOLAP, stats, models, data mining)

W6: Define **BI Vendors**

create bI and analytical software purchased by businesses (via the cloud)

What does **analytics** use and how is it useful?

* data, information technology, statistical analysis, quantitative methods, and mathematical or computer based models
* helps managers gain improved insight about their business operations and make better, fact based decisions

W6: Define **Metrics** (data analytics)

used to quantify performance

W6: Define **Measures** (data analytics)

numerical values of metrics

W6: Define **Discrete Metrics** (data analytics)

involve counting

* on time or not on time
* number or proportion of on time-deliveries

W6: Define **Continuous Metrics** (data analytics)

measured on a continuum

* delivery time
* package weight
* purchase price

W6: **Numerical Data** (data type)

data that consists of numbers and can be measured or quantified (discrete and continuous data)

W6: What are the two sub-topics of numerical data (data type)

1. interval
2. ratio

W6: What is **Interval** numerical data (data type)

* ordinal data but with constant different observations
* no true ‘zero point’
* ratios are not meaningful
* e.g., temperature readings or grades

W6: What is **Ratio** numerical data (data type)

* continuous values
* a natural ‘zero point’
* ratios are meaningful
* e.g., monthly sales or delivery times

W6: Categorical data (data type)

represents qualitative or descriptive characteristics. It consists of categories or groups that are mutually exclusive and do not have a numerical value.

* e.g., gender (male/female), color (red/blue/green), and marital status (single/married/divorced). I

W6: What are the **two** sub-topics of categorical data (data type)

1. nominal
2. ordinal

W6: What is nominal data (data type)

* data placed in categories according to a specified characteristics
* no relationship between categories
* no natural order or ranking
* binary nominal data is where there are only two possible responses
* e.g., customer location or employee classification

W6: What is ordinal data (data type)

* data ranked or ordered according to some relationship with one another that allows sorting
* no fixed units of measurement
* e.g., survey responses (poor, average, good, excellent) or college football rankings

W6: Define Data warehouse

set of databases designed to support decision making in an organization

* aggregate enormous amounts of data from different operating systems
* structured for fast online queries and exploration

W6: Define Data mart

structured databased or databases focused on addressing the concerns of a specific problem or business unit

* e.g., increasing customer retention or improving product quality

W6: Define **Data Lake**

allow for storage of data in both structured as well as unstructured (raw) formats)

* provide tools to pipe out data, filter it and refine it so it can be turned into information

W6: Define **Data Cloud**

cloud service that provides tools to extract transform and load (ETL) data from disparate sources into the cloud so it can be analyzed

* consider flexibility, scalability, cost-effectiveness and fault tolerance

W6: What are the **three big V’s** of big data

1. Volume
2. Velocity
3. Variety

W6: Define **Data Governance**

* rules and processes needed to manage data from creation to retirement


* Legal, Regulatory, Privacy, Information Security and Operation considerations

W6: What are things you need to consider **before** building a large scale data warehouse?

* clear vision with business focused objectives and issues
* communicate with executives and make sure they understand the payoff/ROI

W6: What are the types of data analytics?

W6: What should you do when applying data analytics?

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W6: Why does Business Analytics **matter** to A&F?

W6: What are the **differences** between data and information?

* **Data**: raw facts and figured
* **Information**: data presented in a context so that it can answer or question or support decision-making
* **Knowledge**: insight derived from experience and expertise (based on data and information)

Can you classify the data elements in this purchasing database?

W6: Define **Big Data**

* the collections, storage and analysis of extremely large complex and often unstructured datasets that can be used by organizations to generate insights that would otherwise be impossible to make
* decision-making is data-driven, fact-based and enabled by:
* standardized corporate data
* access to third-party data sets through cheap, fast computing, and easier-to-use software

W8: Define **Artificial Intelligence (AI)**

computer software that can mimic or __improve__ upon functions that would otherwise require human intelligence

* recall Moore’s Law - computer power doubles approx. every 2 years

W8: What are the **two major types** of artificial intelligence

W8: What are the two sub-categories of the major AI types?

1. **Supervised Learning**


1. algorithms trained by specific examples and classifications
2. e.g., Gmail email spam filters learn to classify emails as “spam” or “not spam” by recognizing patterns and features in emails
2. **Unsupervised Learning**


1. algorithms that are not fed a pre-determined result
2. e.g., Facebook’s “People You May Know” feature, uses ‘clustering’ to identify patterns in user data without being told what to look for


1. # of connections with people who attend the same school as you

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W8: Define **Graphic Processing Unit** (GPU)

designed for specific tasks like handing large blocks of data simultaneously (parallel process)

* more efficient in intense AI computations

W8: Define **Central Processing Unit** (CPU)

more general, handles sequential processing tasks

W8: Define **Neural Network**

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W8: Define **Expert Systems**

W8: What is an **algorithm**

set of instructions that tell a computer system what to do

* AI uses algorithms in its process but can modify and improve it based on data it encounters

W8: Define **Generative AI**

describes AI that can be used to create new content, including text, audio, images, video, code and simulations

* sub category of machine learning

W8: Define **Large Language Models** **(LLM)**

* specifically trained to generate human like text
* learn from statistical patterns in language
* a prediction model

W8: Define **Pre-Trained Transformer (GPT)**

a specific type of LLM that basically predicts the next word in a sentence based on statistical patterns

* don’t actually comprehend the meaning of text put in front of them
* strength in being able to consider context from both past and future inputs simultaneously

W8: What are **Tokens**

* concept in LLMs
* represents a word or part of a word
* in LLM, process text by breaking it down into tokens - words or chunks of characters
* 1 token corresponds to 4 characters of text (\~75% of a word)

W9: Define **Autopilot**

allows AI to make __all__ the decisions

* e.g, Tesla autopilot has the vehicle making all of the decisions without human intervention

W9: Define **Co-pilot**

involves AI __assisting__ humans in making information decisions

* e.g., co-pilot in a Tesla vehicle involves the driver being in control, while Tesla’s software features assist in various ways

W9: Why should we treat LLM as a co-pilot?

* imperfect and make mistakes
* as a result of going beyond its training data or misinterpreting a prompt
* cannot be left unattended
* not humans
* tools - require proper use to get the most out of them
* LLM outputs should be a starting point not end point

W9: Define **Hallucination** (in terms of LLM)

* perceptions of something that is not actually present
* many reject this term because it misrepresents what’s happening and suggest AI has human like features
* the model generates information or details that are not present in the input or the original context. It involves the model creating content that goes beyond the actual data it has been provided or the knowledge it has learned.

W9: Define **Confabulation** (in terms of LLM)

* Confabulation can happen when a language model generates responses that seem coherent but are factually incorrect, misleading, or nonsensical. It's one of the challenges in working with large language models, as they can generate text that sounds good on the surface but may not be accurate or reliable.

W9: Define **Prompt Engineering**

optimizing textual input to effectively communicate with large language models

W9: How will roles like software engineering change?

W9: What are important factors when creating an effective prompt?

* choosing your words deliberately
* think about sentence construction
* correct grammar (avoid confusing LLM)
* be precise - give clear constraints in the prompt

W9: Define the **Value Chain**

a set of activities through which a product or service is created and delivered to customers

W9: What are the components of the Value Chain and key resources?

W11: What is the formula to formulating an effective prompt?

W11: What are the four steps in Prompt Priming

1. **Problem Formulation** - determining what to ask the AI (think first)
2. **Exploration** - using major AI (get creative)
3. **Critical Thinking** - weeding out poor AI context (fact check & edit)
4. **Reflection** - AI is here to add/improve, not replace (learn & improve)

W11: What is **Domain Specific** and its **importance**

* remixes the concept of LLMs by using smaller models that are trained on a subset of the larger data set along with proprietary first party data
* complex and unique language within certain industries that warrant a different approach
* Bloomberg is experimenting with internal corporate AI models

W11: AI & Healthcare

W11: AI & Product Development

W11: What are some issues that are arising as a result of Generative AI’s popularity

W11: What are some potential risks of AI?

W11: What needs to be considered when implementing AI in the **legal** field?

W11: What needs to be considered when implementing AI: **Organizational**

W11: What needs to be considered when implementing AI: **Societal**

W11: What needs to be considered when implementing AI: **Ethical**

W11: Define **Disruptive Technologies**

technologies that create market shocks and catalyze growth (aka disruptive innovation)

* based on the concept of giant killing market shocks that knock off and displace once-dominant (**incumbent**) firms, including their product and market alliances
* often powered by a shift from atoms to bits (software)

W11: What are characteristics of disruptive technology?

W11: Define **Sustaining Innovation**

occurs when a company creates a better performing product to sell for higher profits to its existing customers

* leveraged by already successful companies in their industries
* motivation is profit: better products, pursue even higher profit margins
* not a successful in isolation
* better performance and lower cost

W11: When does disruptive innovation **occur**?

when a company with fewer resources (and often a lower performing product) move upmarket to challenge the incumbent’s core business

W11: Define **low end disruption**

company uses a low cost business model to enter at the bottom of an existing market and claim a segment, causing the incumbent to retreat upmarket to make higher margins

* form of asymmetric motivation

W11: Define **new market disruption**

company creates and claims a new segment in an existing market by catering to an undeserved or neglected customer base, slowly improving in quality until incumbent businesses are obsolete (out of date)

W11: How is **not** all innovation disruptive

W11: What is a disruptor’s strategy to creating a low-end disruption?

W11: What is a disruptor’s strategy to creating a new market disruption?

W11: Why do Incumbent firms fail?

*** last one: “startups amass expertise quickly. big firms forced to play catch-up. few ever close the gap with new* __*leaders*__

W11: What should you do if a potential disruptor is spotted?

W11: What is the big bang disruption

W11: Describe the Traditional Technology Adoption Curve

* new technology is adopted slowly in stages by a series of customer types


1. starts with a small group of innovators
2. moves to early adopters
3. then moves to cross the ‘chasm’ to early majority and then the late majority
4. and eventually picks up the laggards

W11: Describe the differences between the Trad. Tech Adoption Curve and Big Bang Disruption

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W11: What are **three characteristics** of Big Bang Disruption

* e.g., Spotify
* buying and downloading mp3s vs unlimited streaming for a monthly subscription
* apple was even put on the defensive here and responded with Apple Music

W11: What are the **defining** characteristics of Big Bang Disruption

W12: How does Disney integrate technology into usual manual experiences?

The MagicBand which is part of their MyMagic+ system. It can be used:

* for park and attraction admission
* for keyless entry to your hotel room
* to pay for rides
* to locate you to deliver restaurant meals

W12: What costs does Disney incur for each MagicBand user?

W12: What costs does Disney incur for each user of the MagicMobile app?

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W12: What are the financial benefits when software (app) replaces hardware (band)?

W12: What is an **Internet of Things (IoT) device**?

any computing device with the ability to transfer data over a network

W12: How is IoT important for CPAs and CFAs?

W12: How do businesses benefit from the use of IoTs?

* increase productivity
* automate process
* optimize value chain
* improve customer experience
* create new business models

W12: Explain the IoT **device** risks and mitigation strategies

W12: Explain the IoT **data storage** risks and mitigation strategies

W12: Explain the IoT data breach risks and mitigation strategies

W12: Explain the IoT network risks and mitigation strategies

W12: Explain the IoT employee risks and mitigation strategies

W12: What is **Blockchain**?

* a digital system of record that is a decentralized, distributed ledger system where the transactions or ownership are recorded and verified across many computers in a network (peer-to-peer nature of blockchain)
* the transactions/associated data are bundled into digital blocks and are linked using cryptography, forming a chain
* highly resistant to modification (immutable -inchangable)

W12: Describe how blockchain works

W12: Define **Cryptocurrency**

a digital asset where a secure form of mathematics (cryptography) is used to handle transactions, control the creation of additional units and verify the transfer of assets

W12: Define **Bitcoin**

an open source, decentralized payment system that operates in a peer-to-peer environment without a bank or a central authority