Chapter 12: Business Analytics & Technology Guide 4: Artificial Intelligence

Question 1

Define Business Analytics (BA) and Business Intelligence

Answer 1

Business analytics (BA): is the process of developing decisions based on insights generated from historical data

• answer questions such as: What happened, how many, how often, where is the problem, what actions are needed, why is this happening, what will happen if these trends continue, what will happen next?

Business intelligence (BI) applications, technologies, and processes are gathering, storing, accessing, and analyzing data to help business users make better decisions

Question 2

Describe the decision-making
process (or “types” of decisions)

Answer 2

Structured decisions: deal with routine and repetitive problems for which standard solutions exist

• for lower managers

Unstructured decisions: These decisions are intended to deal with “fuzzy,” complex problems for which there are no cut-and-dried solutions

• for senior managers

Semi structured decisions: in which only some of the decision-process phases are structured and also involve personal judgment

Question 3

Describe the three business analytics targets.

Answer 3

Organizations use BA for:

The development of one or a few related analytics applications: This target is often a point solution for a departmental need, such as campaign management in marketing.

The development of infrastructure to support enterprise-wide analytics: This target supports both current and future analytics needs.

Support for organizational transformation: With this target, a company uses business analytics to fundamentally transform the ways it competes in the marketplace

Question 4

BA process begins with a business problem, often called ___ ____.

Answer 4

pain points

Question 5

Describe the business analytics process.

Answer 5

• The business analytics (BA) process begins with identifying business problems (pain points).
• Key technologies include microprocessors, GPUs, digital storage, and high-speed networks.
• Data management involves gathering both internal (structured) and external (unstructured, e.g., social media) data, forming Big Data.
• BA includes Descriptive Analytics (historical data), Predictive Analytics (forecasting), and Prescriptive Analytics (decision recommendations).
• Presentation tools like dashboards visually communicate insights.
• Decision-makers play a crucial role by being ready to “ask the next question,” requiring intuition and creativity.

Question 6

Describe the purpose of descriptive analytics.

Answer 6

Descriptive analytics summarizes what has happened in the past and enables decision makers to learn from past behaviours.

• Ex. Average dollars spent per customer, year-over-year change in sales

Question 7

Discuss the BA tools that are commonly used in descriptive analytics.

Online analytical processing (OLAP), Data mining,Decision-support system

Answer 7

Online analytical processing (OLAP): allows for the dynamic “slicing and dicing” of data to view specific details, drill down for deeper insights, or roll up for a broader perspective

Data mining: refers to the process of searching for valuable business information in a large database, data warehouse, or data mart.

Decision-support systems (DSSs): combine models and data to analyze semi structured problems and some unstructured problems that involve extensive user involvement

Sensitivity analysis examines how sensitive an output is to any change in an input while keeping other inputs constant.

• Ex. For instance, how much will the monthly mortgage payment change if the mortgage rate is increased by 0.2, 0.3, and 0.5 percentage points?

What–if analysis: attempts to predict the impact of changes in the assumptions—that is, the input data—on the proposed solution

Goal-seeking analysis: represents a “backward” solution approach. Attempts to calculate the value of the inputs necessary to achieve a desired level of output

Question 8

Describe the purpose of predictive analytics.

Answer 8

Predictive analytics: examines recent and historical data to detect patterns and predict future outcomes and trends

• Predictive analytics can only forecast what might happen in the future NOT will happen

Question 9

Discuss the BA tools that are commonly used in predictive analytics.

Answer 9

Data mining: can predict trends and behaviours.

• For example, targeted marketing relies on predictive information. Data mining can use data from past promotional mailings to identify those prospects who are most likely to respond favourably to future mailings.

Question 10

Describe the purpose of prescriptive analytics.

Answer 10

Prescriptive analytics goes beyond descriptive and predictive models by recommending one or more courses of action and by identifying the likely outcome of each decision

• it suggests multiple future outcomes based on the decision maker’s actions.

Question 11

Discuss the BA tools that are commonly used in prescriptive analytics.

Answer 11

optimization, simulation, and decision trees

• (used in order to help make decisions)

Question 12

Discuss why presentation tools are so valuable in the business analytics process.

define data visualization as well

Answer 12

organizations use presentation tools to display the results of analyses to users in visual formats such as charts, graphs, figures, and tables.

• This process, known as data visualization, makes the results more attractive and easier to understand

Question 13

What is a dashboard? Why are dashboards so valuable to an organization’s decision makers?

+ define Management Cockpit Room

Answer 13

Dashboard: provides easy access to timely information and direct access to management reports. It is user-friendly, it is supported by graphics, enables managers to examine exception reports and drill down into detailed data

Management Cockpit Room: The cockpit-like arrangement of instrument panels and displays helps managers visualize how all of the different factors in the business interrelate.

Question 14

What is artificial intelligence?

Answer 14

Artificial intelligence (AI): as the theory and development of information systems able to perform tasks that normally require human intelligence

• The ultimate goal of AI is to build machines that mimic human intelligence

Question 15

Differentiate between artificial and human intelligence.

Answer 15

Humans intelligence
* Peservation of knowledge: Perishable
* Dissemination of knowledge: difficult and expensive task
* Recognizing patterns: fast, easy to explain
* Reasoning: use wide of experiences
* Creativity: high

AI
* Peservation of knowledge: Permanent
* Dissemination of knowledge: easy, fast
* Recognizing patterns: worse/better (depending on case)
* Reasoning: narrow view
* Creativity: low

Question 16

Strong vs Weak AI

Answer 16

Strong AI: is hypothetical artificial intelligence that matches or exceeds human intelligence—the intelligence of a machine that could successfully perform any intellectual task

Weak AI: performs a task that once required human intelligence to perform, and does so at human levels or better

Question 17

Describe the four stages of AI applications.

Answer 17

First stage: Consists mainly of recommendation systems. These systems learn from vast amounts of data to personalize online content for each of us

Second stage: analyze the data that traditional companies have collected and labelled in the past.

Third-stage: analyze additional data from smart devices and sensors

Fourth stage: integrate the three previous stages and enable machines to sense and respond to the world around them.

• Ex. autonomous vehicles navigate roads and traffic

Question 18

Define expert systems and describe some problems that expert systems have.

Answer 18

Expert systems (ESs): are computer systems that attempt to mimic human experts by applying expertise in a specific domain. Expert systems can either support decision makers or completely replace them.

• Ex. Google Maps, Navigator
• Ex. Medical expert systems used to diagnosis patients

Problem:
Transferring domain expertise from human experts to the expert system can be difficult because humans cannot always explain how they know and what they know. They are often not aware of their complete reasoning process.

Question 19

Differentiate between machine learning and deep learning.

Answer 19

Machine learning (ML): is the ability to accurately perform new, unseen tasks, built on known properties learned from training or historical data that are labelled

• Ex. In banking, automated fraud detection systems use machine learning to identify behaviour patterns that could indicate fraudulent payment activity.

Deep learning: is a subset of machine learning in which the system discovers new patterns without being exposed to labelled historical or training data

• Ex. eBay is using deep learning to categorize products in images posted by sellers. By studying images that have already been tagged, the system can tell the difference (ex. between a pair of flip-flops and a pair of flats).

Question 20

Describe how neural networks function.

Answer 20

Neural network: is a set of virtual neurons or central processing units (CPUs) that work in parallel in an attempt to simulate the way the human brain works, although in a greatly simplified form

• A neural network is a computer system designed to mimic the way the human brain works, especially in terms of learning and problem-solving

Question 21

Describe the advantages of computer vision, natural language processing, and speech recognition.

(define)

Answer 21

Computer vision: refers to the ability of information systems to identify objects, scenes, and activities in images.

• Ex. Pinterest is using a computer vision system combined with deep learning to enhance product recommendations by automatically recognizing specific objects contained within the image of a pin.

Natural language processing refers to the ability of information systems to work with text the way that humans do. For example, these systems can extract the meaning from text and can generate text that is readable, stylistically natural, and grammatically correct.

• Ex. Built into Google’s translation app, deep learning technology has the ability to translate printed text such as menus in a live view through your phone’s camera

Speech recognition focuses on automatically and accurately transcribing human speech.

• Applications include medical dictation, hands-free writing, voice control of information systems, and telephone customer service applications.

Question 22

What are cobots?

Answer 22

cobots (cooperative robots) that share jobs with humans on the factory floor, robotic vacuum cleaners, and so on

Question 23

Describe how you might use intelligent agents, information agents, monitoring and surveillance agents, and user agents.

Answer 23

Intelligent agent is a software program that assists you, or acts on your behalf, in performing repetitive computer-related tasks

Information agents: search for information and display it to users.

Monitoring and surveillance agents: constantly observe and report on some item of interest

• Ex. Monitoring and surveillance agents can watch your competitors and notify you of price changes and special offers.

User agents: take action on your behalf

• Ex. Check your email, sort it according to your priority rules, and alert you when high-value emails appear in your inbox. & Automatically fill out forms on the web for you.