Chapter 16

Question 1

loyalty program

Answer 1

Systems that provide rewards and usage incentives, typically in exchange for a method that provides a more detailed tracking and recording of customer activity. In addition to enhancing data collection, loyalty cards can represent a significant switching cost.

Question 2

online analytical processing (OLAP)

Answer 2

A method of querying and reporting that takes data from standard relational databases, calculates and summarizes the data, and then stores the data in a special database called a data cube.

Question 3

data mart

Answer 3

A database or databases focused on addressing the concerns of a specific problem (e.g., increasing customer retention, improving product quality) or business unit (e.g., marketing, engineering).

Question 4

data cube

Answer 4

A special database used to store data in OLAP reporting.

Question 5

database management system (DBMS)

Answer 5

Sometimes referred to as database software; software for creating, maintaining, and manipulating data.

Question 6

Hadoop

Answer 6

A set of mostly open source tools to manage massive amounts of unstructured data for storage, extraction, and computation.

Question 7

query tools

Answer 7

A tool to interrogate a data source or multiple sources and return a subset of data, possibly summarized, based on a set of criteria.

Question 8

transaction

Answer 8

Some kind of business exchange.

Question 9

analytics

Answer 9

A term describing the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.

Question 10

data mining

Answer 10

The process of using computers to identify hidden patterns in, and to build models from, large datasets.

Question 11

CAPTCHAs

Answer 11

An acronym standing for completely automated public Turing test to tell computers and humans apart. The Turing test is, rather redundantly, an idea (rather than an official test) that one can create a test to tell computers apart from humans.

Question 12

OCR

Answer 12

Optical Character Recognition. Software that can scan images and identify text within them.

Question 13

data

Answer 13

Raw facts and figures.

Question 14

self-supervised learning

Answer 14

Sometimes called unsupervised learning, where systems build pattern-recognizing algorithms using data that has not been pre-classified.

Question 15

ETL

Answer 15

Extract, Transform, Load—copying data from multiple, disparately organized data sources, transforming (or cleaning) the data into a common format, and loading it into a combined usable format. ETL is a key step in getting data into a data warehouse or data mart.

Question 16

neural networks

Answer 16

Statistical techniques used in AI and particularly in machine learning. Neural networks hunt down and expose patterns, building multilayered relationships that humans can’t detect on their own.

Question 17

change management

Answer 17

Refers to techniques to facilitate organization change, including preparing individuals for change and offering training and support during and after implementation. Change management is especially important in IS use, as many information systems implementations involve radical change to the way a firm conducts business or the way individuals and teams operate within the organization.

Question 18

information

Answer 18

Data presented in a context so that it can answer a question or support decision-making.

Question 19

omnichannel

Answer 19

Providing customers with a unified experience across customer channels, which may include online, mobile, catalog, phone, and retail. Pricing, recommendations, and incentives should reflect a data-driven, accurate, single view of the customer.

Question 20

knowledge

Answer 20

Insight derived from experience and expertise.

Question 21

Python

Answer 21

A general purpose programming language that is also popular for data analytics.

Question 22

legacy systems

Answer 22

Older information systems that are often incompatible with other systems, technologies, and ways of conducting business. Incompatible legacy systems can be a major roadblock to turning data into information, and they can inhibit firm agility, holding back operational and strategic initiatives.

Question 23

Turing test

Answer 23

Conceived by Alan Turing, a Turing test of software’s ability to exhibit behavior equivalent to, or indistinguishable from, a human being.

Question 24

row or record

Answer 24

A row in a database table. Records represent a single instance of whatever the table keeps track of (e.g., student, faculty, course title).

Question 25

column or field

Answer 25

A column in a database table. Columns represent each category of data contained in a record (e.g., first name, last name, ID number, date of birth).

Question 26

table or file

Answer 26

A list of data, arranged in columns (fields) and rows (records).

Question 27

relational database

Answer 27

The most common standard for expressing databases, whereby tables (files) are related based on common keys.

Question 28

dynamic pricing

Answer 28

Dynamic ticket pricing use takes off, and teams hope it’ll lure fans back into sports stadiums.

Question 29

artificial intelligence

Answer 29

Computer software that can mimic or improve upon functions that would otherwise require human intelligence.

Question 30

structured query language (SQL)

Answer 30

A language used to create and manipulate databases.

Question 31

business intelligence (BI)

Answer 31

A term combining aspects of reporting, data exploration and ad hoc queries, and sophisticated data modeling and analysis.

Question 32

data warehouse

Answer 32

A set of databases designed to support decision-making in an organization.

Question 33

dashboards

Answer 33

A heads-up display of critical indicators that allow managers to get a graphical glance at key performance metrics.

Question 34

R

Answer 34

A programming language specifically created for analytics, statistical, and graphical computing.

Question 35

semi-supervised learning

Answer 35

A type of machine learning where the data used to build models contains data with explicit classifications, but is also free to develop its own additional classifications that may further enhance result accuracy.

Question 36

data lake

Answer 36

A catch-all term for storage and access technologies used in Big Data. Data lakes are systems that allow for the storage of data in both structured as well as “raw,” “unfiltered” formats. Data lakes also provide the tools to “pipe out” data, filter it, and refine it so that it can be turned into information.

Question 37

data cloud

Answer 37

Sometimes referred to as cloud data warehousing, this term refers to a cloud service that provides tools to extract and transform data from disparate sources so that it can be interrogated as needed. Unlike data warehouses, data lakes, or similar tools that an organization might run on-site, a data cloud can be spun up to temporarily hold a very large amount of data for short-term use, then disbanded when it is no longer needed. Snowflake is the best known of the many firms providing services in this space.

Question 38

shallowfakes

Answer 38

Manipulating media without the using artificial intelligence. Examples might include using Photoshop or simply slowing down a video and passing the distortion off as truth.

Question 39

transaction processing systems (TPS)

Answer 39

Systems that record a transaction (some form of business-related exchange), such as a cash register sale, ATM withdrawal, or product return.

Question 40

canned reports

Answer 40

Reports that provide regular summaries of information in a predetermined format.

Question 41

genetic algorithms

Answer 41

AI technologies that seek an optimal model by transforming or “mutating” an algorithm (versus neural networks, which add weights and mappings to a combination of inputs)—iteratively testing the result and choosing the best outcome.

Question 42

Big Data

Answer 42

A general term used to describe the massive amount of data available to today’s managers. Big Data are often unstructured and are too big and costly to easily work through use of conventional databases, but new tools are making these massive datasets available for analysis and insight.

Question 43

data visualization

Answer 43

The graphical representation of data and information.

Question 44

database

Answer 44

A single table or a collection of related tables.

Question 45

serverless computing

Answer 45

A type of cloud computing where a third-party vendor manages servers, replication, fault-tolerance, computing scalability, and certain aspects of security, freeing software developers to focus on building “Business Solutions” and eliminating the need to spend time and resources managing the technology complexity of much of the underlying “IT Solution.”

Question 46

graphical query tools

Answer 46

Allow a user to create a query through a point-and-click or drag-and-drop interface, rather than requiring programming knowledge.

Question 47

machine learning

Answer 47

A type of artificial intelligence that leverages massive amounts of data so that computers can improve the accuracy of actions and predictions on their own without additional programming.

Question 48

database administrator (DBA)

Answer 48

Job title focused on directing, performing, or overseeing activities associated with a database or set of databases. These may include (but not necessarily be limited to): database design, creation, implementation, maintenance, backup and recovery, policy setting and enforcement, and security.

Question 49

data aggregators

Answer 49

Firms that collect and resell data.

Question 50

ad hoc reporting tools

Answer 50

Tools that put users in control so that they can create custom reports on an as-needed basis by selecting fields, ranges, summary conditions, and other parameters.

Question 51

over-engineer

Answer 51

Build a model with so many variables that the solution arrived at might only work on the subset of data you’ve used to create it.

Question 52

deep learning

Answer 52

A type of machine learning that uses multiple layers of interconnections among data to identify patterns and improve predicted results. Deep learning most often uses a set of techniques known as neural networks and is popularly applied in tasks like speech recognition, image recognition, and computer vision.

Question 53

e-discovery

Answer 53

The process of identifying and retrieving relevant electronic information to support litigation efforts.

Question 54

supervised learning

Answer 54

A type of machine learning where algorithms are trained by providing explicit examples of results sought, like defective versus error-free, or stock price.

Question 55

expert systems

Answer 55

A set of technologies used in the development of AI systems that use a set of programmed decision rules or example outcomes to perform a task in a way that mimics applied human expertise.

Question 56

deepfake

Answer 56

Creates bogus media—images, sound, or video—created by artificial intelligence that distort media in a way that makes it appear that a false event actually took place.