chapter 15, 16, 17, 18 Flashcards
Exam 3 (277 cards)
1
Q
computing hardware
A
The physical components of information technology, which can include the computer itself plus peripherals such as storage devices, input devices like the mouse and keyboard, output devices like monitors and printers, networking equipment, and so on.
2
Q
software
A
A computer program or a collection of programs. It is a precise set of instructions that tells hardware what to do.
3
Q
operating system
A
the software that controls the computer hardware and establishes standards for developing and executing applications
ex: WIndows, Mac OS X, iOS, Linux
4
Q
applications
A
includes desktop programs, enterprise software, utilities, and other programs that perform specific tasks for users and organizations.
—a range of which include end-user programs like those in Office, apps that run on smartphones, and the complex set of programs that manage a business’s inventory, payroll, and accounting
5
Q
user interface (UI)
A
The mechanism through which users interact with a computing device.
The UI includes elements of the graphical user interface (or GUI, pronounced “gooey”), such as windows, scroll bars, buttons, menus, and dialogue boxes, and can also include other forms of interaction, such as touch screens, motion sensing controllers, or tactile devices used by the visually impaired.
6
Q
firmware
A
Software stored on nonvolatile memory chips (as opposed to being stored on devices such as hard drives or removable discs). Despite the seemingly permanent nature of firmware, many products allow for firmware to be upgraded online or by connecting to another device.
Control programs stored on chips
7
Q
Base Input/Output System (BIOS)
A
the base-level commands for controlling a hardware device
This often includes commands to read files from storage and execute a program, and commands necessary for booting an operating system when a device is restarted.
The BIOS is considered a more “low-level” set of control code than the operating system
8
Q
embedded systems
A
Special-purpose software designed and included inside physical products (often on firmware).
Embedded systems help make devices “smarter,” sharing usage information, helping diagnose problems, indicating maintenance schedules, providing alerts, or enabling devices to take orders from other systems.
9
Q
platform
A
Products and services that allow for the development and integration of software products and other complementary goods.
Windows, iOS, Android, and the standards that allow users to create Facebook apps are all platforms.
10
Q
application software (aka software applications or apps)
A
performs the work that users and firms are directly interested in accomplishing
the more application software that is available for a platform (the more games for a video game console, the more apps for your phone or AR/VR headset), the more valuable that it potentially becomes
11
Q
desktop software
A
Applications installed on a personal computer, typically supporting tasks performed by a single user.
your browser, your Office suite (e.g., word processor, spreadsheet, presentation software), photo editors, and computer games are all desktop software
12
Q
enterprise software
A
Applications that address the needs of multiple users throughout an organization or work group
Most companies run various forms of enterprise software programs to keep track of their inventory, record sales, manage payments to suppliers, cut employee paychecks, and handle other functions
13
Q
software package
A
a software product offered commercially by a third party
14
Q
enterprise resource planning (ERP)
A
A software package that integrates the many functions (accounting, finance, inventory management, human resources, etc.) of a business
The leading ERP vendors include the firms SAP and Oracle
A company also doesn’t have to install all of the modules of an ERP suite, but it might add functions over time. Although a bit more of a challenge to integrate, a firm can also mix and match components, linking software the firm has written with modules purchased from different enterprise software vendors.
15
Q
customer relationship management (CRM)
A
part of the ERP system:
systems used to support customer-related sales and marketing activities
16
Q
supply chain management (SCM)
A
part of ERP system
systems that can help a firm manage aspects of its value chain, from the flow of raw materials into the firm through delivery of finished products and services at the point-of-consumption
17
Q
business intelligence systems (BI)
A
part of ERP system
use data created by other systems to provide reporting and analysis for organizational decision-making
18
Q
database management system (DBMS)
A
Sometimes referred to as database software; software for creating, maintaining, and manipulating data.
considered an application itself
Many ERP systems are configured to share the same database system for efficiency (or else will have issues with managing the value chain)
19
Q
the ___ system stores and retrieves the data an ___ creates and uses
A
database, app
20
Q
distributed computing
A
A form of computing where systems in different locations communicate and collaborate to complete a task
Distributed computing can yield enormous efficiencies in speed, error reduction, and cost savings and can create entirely new ways of doing business
21
Q
server
A
hardware context: a computer that has been configured to support requests from other computers (e.g., Dell, IBM, and HP sell servers)
software context: a program that fulfills requests (e.g., the Apache open source Web server)
22
Q
why do many firms choose not to own the applications or any of their server hardware at all?
A
they pay third-party firms to host their software “in the cloud”
This option is particularly attractive for smaller firms that can’t or don’t want to invest in the expense and expertise associated with owning and operating hardware, for firms looking for extra computing capacity, and for firms that want public servers (e.g., websites) to be in fast, reliable locations outside of a company’s own private network.
23
Q
client-server system
A
client: A software program that makes requests of a server program.
server: Program that fulfills the requests of a client
24
Q
application server
A
Software that houses and serves business logic for use (and reuse) by multiple applications
25
web services
Small pieces of code that are accessed via the application server and permit interoperable machine-to-machine interaction over a network
served up by the app server are programmed to perform different tasks: returning a calculation, accessing a database program, make a request to another server in another org, or use AI to return result of an AI query
26
APIs
Programming hooks, or guidelines, published by firms that tell other programs how to get a service to perform a task such as send or receive data.
For example, Amazon.com provides APIs to let developers write their own applications and websites that can send the firm orders.
27
service-oriented architecture (SOA)
A robust set of Web services built around an organization's processes and procedures
makes systems more flexible,
code can be reused,
each layer can be separately maintained, upgraded, or migrated to new hardware with little impact on others
28
Expedia Affiliate Network
generates business values with APIs
Expedia offers APIs that allowed partner firms to integrate Expedia's tech and inventory into their own websites and apps
United, Aer Lingus, Greyhound all use it
Pro for partners: they get to keep customers in their websites for a greater percentage of travel needs, partner firm continues to maintain the relationship with the customer (and gather critically important customer data), and they get a cut of Expedia’s booking revenue
pro for Expedia: Expedia gets distribution—many more orders than it would otherwise get through its own sites and apps
29
electronic data interchange (EDI)
a set of standards for exchanging information between computer applications
most often used as a way to send the electronic equivalent of structured documents between different organizations
Using EDI, each element in the electronic document, such as a firm name, address, or customer number, is coded so that the receiving computer program can recognize it.
Eliminating paper documents makes businesses faster and lowers data entry and error costs.
30
extensible markup language (XML)
A tagging language that can be used to identify data fields made available for use by other applications.
is a markup language that defines a set of rules for encoding documents in a format that is both human-
readable and machine-readable
Many computer programs also use XML as a way to export and import data in a common format that can be used regardless of the kind of computer hardware, operating system, or application program used
easier to code than EDI, and orgs can create formats to represent any kind of data
31
what two main technologies are replacing EDIs?
extensible markup language (XML) and JavaScript Object Notation (JSON)
32
JavaScript Object Notation (JSON)
a technology standard often used to format data when being sent or received via APIs
33
programming language
Provides the standards, syntax, statements, and instructions for writing computer software
many commercial applications are written in a variant of the C programming language
34
frameworks
libraries, templates, and extensions that simplify and standardize common tasks, speeding software development, reducing errors, and prompting reuse
Programmers use frameworks to use a standardized set of code and techniques that others have developed and tested, rather than requiring every developer to create his or her own code for things many others have done before them
Rails (for Ruby), Django (for Python), AngularJS (for JavaScript), and ASP.NET
35
integrated development environment (IDE)
An application that includes an editor (a sort of programmer’s word processor), debugger, and compiler, among other tools.
many companies provide IDEs for free to encourage software development like Xcode for Apple products, Android Studio from Google, Visual Studio from Microsoft
36
compile
Step in which program code written in a language that humans can more easily understand, is then converted into a form (expressed in patterns of ones and zeros) that can be understood and executed by a microprocessor. (translator)
Programmers using conventional programming languages must compile their software before making it available for execution
37
Java
A programming language, initially developed by Sun Microsystems, designed to provide true platform independence (“write once, run anywhere”) for application developers.
In most cases, Java apps are developed to be executed by a Java Virtual Machine (JVM)—an interpreting layer that translates code as it executes, into the format required by the operating system and microprocessor.
Without Java, application developers have to write and compile software to execute natively by a specific operating system/microprocessor combination (e.g., Windows/Intel, Linux PowerPC, Mac/Intel, Linux/Intel).
Java has not been popular for desktop applications
38
what's Java's biggest selling point
Java’s platform independence—the ability for developers to “write once, run everywhere”
39
scripting languages
Programming tools that execute within an application.
Scripting languages are interpreted within their applications, rather than compiled to run directly by a microprocessor
this interpretation part makes them slower, but easier to use
40
scripting languages are interpreted within their applications, what does interpreted mean?
Languages where each line of written code is converted (by a software program, called an “interpreter”) for execution at run-time. Most scripting languages are interpreted languages. Many programmers also write Java applications to be interpreted by the Java Virtual Machine.
41
low code/no code (LCNC) environments
Highly visual software development tools that allow users to create information systems with little to no coding required for system development
"software legos"
most often used to create simple systems used internally
LCNC tools are also often used to create front-ends for business analytics efforts—say to select options to run a report or to build a dashboard that displays the current status of some aspect of organizational performances
42
software development methodologies
methods to divide up tasks related to software creation and deployment into tasks targeted at building better products with stronger product management guidelines and techniques
43
software development lifecycle (SDLC)
a process for planning, creating, testing, and deploying an information system.
The SDLC considers that to create and operate an information system, there are typically six steps involved:
planning
analysis
design
testing
implementation,
and maintenance.
44
waterfall method
(the classic, but increasingly out-of-favor approach)
A relatively linear sequential approach to software development (and other projects).
Benefits include surfacing requirements up front and creating a blueprint to follow throughout a project.
Often criticized for being too rigid, slow, and demanding project forethought that’s tough to completely identify early on.
45
feature creep
expansion of the scope of a project
46
agile development
(dominating approach)
Developing work continually and iteratively, with a goal of more frequent product rollouts and constant improvement across smaller components of the larger project.
pros: speed and flexibility
cons: some say it might rush product development w/ less quality and documentation
47
scrum
An approach to organizing and managing agile projects that breaks deliverables into “sprints” delivered in one- to six-week increments by teams of fewer than ten.
Scrum defines functions (roles) for management and development, meetings (ceremonies), and how the process is documented and tracked (artifacts).
48
total cost of ownership (TCO)
An economic measure of the full cost of owning a product (typically computing hardware and/or software). TCO includes direct costs such as purchase price, plus indirect costs such as training, support, and maintenance.
49
marginal cost
The costs associated with each additional unit produced.
50
open source software (OSS)
Software that is free and where anyone can look at and potentially modify the code
51
cloud computing
Replacing computing resources—either an organization’s or individual’s hardware or software—with services provided over the Internet.
52
software as a service (SaaS)
A form of cloud computing where a firm subscribes to a third-party software and receives a service that is delivered online.
With SaaS, you don’t need to own the program or install it on your own computer
application service provider (ASP) & hosted software vendor (HSV)
53
hardware clouds can let firms do what
they can let the firms take their software and run it on someone else's harware
54
virtualization
A type of software that allows a single computer (or cluster of connected computers) to function as if it were several different computers, each running its own operating system and software. Virtualization software underpins most cloud computing efforts, and can make computing more efficient, cost-effective, and scalableh
55
what is Linux?
an open source software operating system
credited with being the most significant product in the OSS arsenal
today, it powers everything from phones to stock exchanges to super computers (makes up 92% of servers in Amazon's AWS cloud)
foundation of the Raspberry Pi OS
56
what is the Raspberry Pi OS?
the operating system for a minuscule single board computer that can be purchased for $10 or less
57
what does the LAMP acronym mean
Linux
Apache Web Server Software
MySQL database
P (Perl, Python or PHP)
58
stack
A software stack is the pieces of software used to build an information system. These may include front-end or client-side code and back-end or server-side code. Other components of a software stack can include the operating system, database, and middleware, among others. Related, a software developer is considered “full stack” if they can code both the customer-facing and server-side portions of an information system.
59
what are software frameworks?
offer pre-built software components, making it faster and easier to write JavaScript code (Angular is a JavaScript framework often used on the Web or front-end, while Express.js is popular on the back-end or server-side JavaScript framework
60
in client server computing, what is the front end referring to?
the front-end is the client-facing code that contains the user interface. This would include Web apps served up in a browser, as well as smart phone apps
61
in client server computing, what is the back end referring to?
In computing, the back-end is server-side code that users do not typically see.
62
MEAN stack
an acronym for popular tools used to build distributed, mostly Web-based applications
MongoDB - database
Express.js - server side API code
AngularJS - JavaScript programming framework
Node.js - server
63
primary reasons firms choose to use OSS over commercial alternatives
cost (free/cheaper OSS)
reliability (more people who look at code, the greater likelihood that errors can be caught and corrected)
security (more eyes = more security vulnerabilities come to light and can be adressed quicker)
scalability (many forms of OSS can be migrated to more powerful hardware)
interoperability (benefit from standardized communication and using similar file formats and software components across hardware)
agility and time to market (by using OSS products, firms can free up time-constrained & difficult-to-hire technical staff to focus on value-added products)
64
security-focused / hardened
describes tech products that contain particularly strong security features
65
what happened with Heartbleed?
Heartbleed was an error in the OpenSSL security toolkit
A routine coding error in the widely distributed software opened a hole that could potentially have been used to allow hackers to gather passwords, encryption keys, and other sensitive information, triggering “the largest security breach in the history of the human race.”
key takeaway: Just because a tool is used by many doesn’t mean one shouldn’t audit its software products to understand the strength of support and potential risks associated with use.
66
how do vendors make money on open source?
selling support and consulting services
selling premium add-ons
67
risks of OSS
certain products are hard to install & maintain (higher TCOs)
Adopters of OSS without support contracts may lament having to rely on an uncertain community of volunteers to support their problems and provide innovative upgrades
Firms adopting OSS may be at risk if they distribute code and aren’t aware of the licensing implications (legal exposure)
68
why has Linux been unsuccessful on desktops?
The small user base for desktop Linux makes the platform less attractive for desktop software developers. Incompatibility with Windows applications, switching costs, and other network effects–related issues all suggest that desktop Linux has an uphill climb in more mature markets.
69
cloud computing
replacing computing resources of either an organization or individual's hardware or software, with services provided over the internet
can be considered by the level of service provided by a cloud vendor
70
what are the 3 most common service levels referred to as?
SaaS, PaaS and IaaS
71
What is PaaS?
Platform as a service
delivers tools so an organization can develop, test, and deploy software in the cloud
(ex: programming languages, database software, product testing & deployment software, and an operating system)
72
What is IaaS?
Infrastructure as a service
offering an organization a more bare-bones set of services that are an alternative to buying its own physical hardware—that is, computing, storage, and networking resources are instead allocated and made available over the Internet and are paid for based on the amount of resources used.
With IaaS, firms get the most basic offerings but can also do the most customization, putting their own tools (operating systems, databases, programming languages) on top.
Typically, the further down this stack you go, the more support and maintenance services your own organization needs to perform (less for SaaS, the most for IaaS, since that’s where a firm heavily customizes and runs its own tech)
73
do SaaS & IaaS need the most or least amount of support and maintenance?
SaaS needs the least amount of support and maintenance
IaaS needs the most
74
how do most SaaS firms earn money?
thru a usage-based pricing model akin to a monthly subscription
others offer free services that are supported by advertising, while others promote the sale of upgraded or premium versions for additional fees
75
what is the most iconic SaaS firm?
Salesforce.com
an enterprise customer relationship management (CRM) provider
76
what are the benefits of SaaS?
forgo large upfront costs of buying and installing software packages
have flexibility (bc firms that adopt Saas never acc buy a system's software & hardware, so these systems become a variable operating expense) to mitigate financial risks associated with making a large capital investment in information systems
makes very sophisticated tech available to smaller firms that otherwise wouldn't be able to afford expensive systems
highly scalable - vendor is responsible for ensuring that systems meet demand fluctuation thru a service level agreement (SLA) (this is important bc many orgs operate in environments prone to wide variance in usage)
moving to the cloud allows companies to optimize their scarce technical talent to focus on their most impactful and strategic work
SaaS firms benefit from economies of scale that not only lower software and hardware costs, but also potentially boost quality
tighter feedback loop in understanding how products are used and why they may fail (might accelerate their ability to enhance their offerings)
SaaS also goes direct to consumers - cut out middle man so can charge less or more, SaaS applications are available everywhere with Wi-Fi (global applications), can address highly specialized markets
reduced risk of software piracy
better for environment since cloud firms more efficiently pool resources to host their tech
77
why do vendors sign a service level agreement (SLA)
to ensure a guaranteed uptime and define their ability to meet demand spikes
78
risks of SaaS
tremendous dependence a firm develops with its SaaS vendor
The cost of operating as a SaaS vendor can be daunting
firms that have to adopt SaaS may find they are forced into adopting new versions, which can result in unforeseen training costs or increase the chance that a user might take an error
SaaS users have a high level of dependance on their internet connection
SaaS means a greater consumerization of technology
Data assets stored off-site—with the potential for security and legal concerns.
Limited configuration, customization, and system integration options compared to packaged software or alternatives developed in-house.
The user interface of Web-based software is often less sophisticated and lacks the richness of most desktop alternatives.
Ease of adoption may lead to pockets of unauthorized IT being used throughout an organization.
79
what are service models?
when firms consider how much tech (software and hardware) will run (by the cloud-computing partner)
80
what is the public cloud?
relying on a third-party provider (like Amazon, Google or Microsoft) to house all components in an information system
81
what are private clouds?
pools of computing resources that a company owns or leases that it doesn't share with other customers
still use cloud computing tech for fast service
ex: Bank of America, CIA
82
what are hybrid clouds?
cloud computing that allows a firm the ability to shift and expand computing from its internal resources (private cloud) to resources provided by an off-site by a cloud computing provider that serves other customers as well (public cloud)
83
cloudbursting
Describes the use of cloud computing to provide excess capacity during periods of spiking demand.
Cloudbursting is a scalability solution that is usually provided as an overflow service, kicking in as needed
Cloudbursting is appealing because forecasting demand is difficult and can’t account for the ultra-rare, high-impact events sometimes called black swans
Planning to account for usage spikes explains why the servers at many conventional corporate IS shops run at only 10 to 20 percent capacity
84
black swans
Unpredicted but highly impactful events.
Scalable computing resources can help a firm deal with spiking impact from black swan events.
The phrase entered the managerial lexicon from the 2007 book of the same name by Nassim Taleb
85
where does cloud computing not work in most situations?
where complex legacy systems have to be ported or where there may be regulatory compliance issues
86
what do clouds do in terms of barriers to entry in the industry?
they can lower them, making it easier for startups to launch and smaller firms to leverage the backing of powerful tech
87
what happens to hardware and software sales as cloud use increases and service revenues increase?
decrease
88
what do server farms require
cheap land
low cost power
ultrafast fiber-optic connections
benefit from mild climates
89
in terms of server farms, what do Google, Oracle's Sun, Microsoft, IBM, and HP all have?
Google, Oracle’s Sun, Microsoft, IBM, and HP have all developed rapid-deployment server farm modules that are preconfigured and packed inside shipping containers.
90
virtualization
A type of software that allows a single computer (or cluster of connected computers) to function as if it were several different computers, each running its own operating system and software. Virtualization software underpins most cloud computing efforts, and can make computing more efficient, cost-effective, and scalable.
91
benefit of virtualization
Firms can stop buying separate servers for each application they want to run.
Instead, organizations can create many virtual computers on a single machine (or cluster of machines that provide a pool of capacity) so hardware is used more efficiently
save a lot of money
increased utilization
reduces a firm's IT based energy consumption
buy and maintain fewer servers, each running at greater capacity
can power down servers until demand increases to use again
them
helps firms scale up
92
containers
A type of virtualization that allows for shared operating systems for more resource savings and faster execution.
However, containers still isolate applications so they execute and move to different computing hardware, just like conventional virtualization
use less resources and execute faster
Docker
93
virtual desktops
another type of virtualization
When a firm runs an instance of a PC’s software on another machine and simply delivers the image of what’s executing to the remote device.
Using virtualization, a single server can run dozens of PCs, simplifying backup, upgrade, security, and administration
allows firms to scale, back up, secure, and upgrade systems far more easily than if they had to maintain each individual PC
94
can virtualization be used in public or private clouds
While virtualization is used to make public cloud computing happen, it can also be used in-house to create a firm’s own private cloud
95
compared with packaged software, what lowers the cost of software distribution and maintenance?
apps
96
several billion-dollar firms have leveraged WHAT as their only or primary interface consumers?
smartphone apps
97
what challenges do mobile apps pose for developers, especially compared against browser-based alternatives?
more challenging updates, version control, and A/B testing
98
what do critics of apps say
they force consumers into smartphone-walled gardens and raise consumer-switching costs
99
Factors that managers should consider when making a make, buy, or rent decision include the following
competitive advantage, security, legal and compliance issues, the organization’s skill and available labor, cost, time, and vendor issues
100
factors must be evaluated over ____
over the lifetime of a project, not just a single point in time
101
managers have numerous options available when determining how to satisfy the software needs of their companies:
purchase packaged software from a vendor, use OSS, use SaaS or utility computing, outsource development, or develop all or part of the effort themselves
102
when would the functions probably not be a good candidate to outsource?
If a company relies on unique processes, procedures, or technologies that create vital, differentiating, competitive advantages
103
what is big data?
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 via use of conventional databases, but new tools are making these massive datasets available for analysis and insight.
104
what is increasingly standardized corporate data and access to rich third-party datasets (leveraged by cheap/fast computing and easier to use software) doing in terms of the new age?
are collectively enabling a new age of data-driven, fact-based decision-making
105
business intelligence (BI)
A term combining aspects of reporting, data exploration and ad hoc queries, and sophisticated data modeling and analysis
106
analytics
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
107
machine learning (ML)
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.
108
dynamic pricing
when a firm sets prices in real or near-real time in order to maximize sales and profits
a pricing strategy in which businesses set flexible prices for products or services based on current market demands
Lion King, Uber or Lyft
109
Beacons
A Bluetooth technology that emits location data to help identify user location. Its uses include distributing real-time promotions and advertising, and to aid in navigation.
(a tech that sends messages to smartphones using a low-energy Bluetooth signal)
110
data
raw facts and figures
111
information
data presented in a context so that it can answer a question or support decision-making
112
knowledge
insight derived from experience and expertise
113
database
a single table or a collection of related tables
114
database management systems (DBMS)
Sometimes referred to as database software; software for creating, maintaining, and manipulating data
Microsoft Access, Intuit Quickbase, Oracle, IBM (DB2) or MySQL
115
who is the world's largest database software vendor?
Oracle
116
structured query language (SQL)
A language used to create and manipulate databases.
LinkedIn, Indeed.com
117
database administrator (DBA)
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.
118
table or file
a list of data, arranged in columns (fields) and rows (records)
119
database
either a single table or a collection of related tables
120
column or field
defines the data that a table can hold
121
row or record
a single instance of whatever the table keeps track of
122
key
the field or fields used to relate tables in a database
can have one-to-many relationships among the keys in these tables (primary and foreign keys)
123
relational databses
The most common standard for expressing databases, whereby tables (files) are related based on common keys
all SQL databases are relational databases
124
NoSQL
avoids SQL and the rigid structure of relational databases
NoSQL technologies are especially popular with Internet firms that rely on massive, unwieldy, and disparately structured data, and this technology is often at the heart of what are often characterized as Big Data efforts.
125
serverless computing
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.”
Google Cloud Firestore & AWS Aurora Serverless
Serverless computing is attractive in projects where it’s OK to have someone else manage the “IT solution” of server, storage, and security, and instead focus on the “business” solution of creating serverless business logic and piping data in and out of serverless storage.
126
transaction processing systems (TPS)
Systems that record a transaction (some form of business-related exchange), such as a cash register sale, ATM withdrawal, or product return.
127
transaction
some kind of business exchange
128
what is the primary source that feeds data to the TPS?
cash register
129
grocers and retailers can tie you to cash transactions if they can convince you to use a what?
loyalty program
130
what's a loyalty program?
A system that provides 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.
131
artificial intelligence (AI)
Computer software that seeks to reproduce or mimic (perhaps with improvements) human thought, decision-making, or brain functions.
132
data aggregators (data brokers)
Firms that collect and resell data.
133
what can be used to supplement a firm's operational data
surveys
134
what can give the firm a competitive edge in terms of data?
Data obtained from outside sources, when combined with a firm’s internal data assets, can give the firm a competitive edge
135
why can data aggregators be bad?
Among other things, they represent a big target for identity thieves, are a method for spreading potentially incorrect data, and raise privacy concerns.
136
legacy systems
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.
mergers and acquisitions only make this worse
137
Airbnb & Data
heavily invests in analytics infrastructure
Airbnb’s “smart pricing” feature uses machine learning to constantly tweak the accuracy of models that suggest the perfect rate
This constantly refined Big Data asset yields big results that keep rental properties full and owner wallets fat, and cements renter loyalty
138
what often limits data utilization?
Legacy systems often limit data utilization because they were not designed to share data, aren’t compatible with newer technologies, and aren’t aligned with the firm’s current business needs.
139
Most transactional databases aren’t set up to be simultaneously accessed for reporting and analysis. In order to run analytics, what needs to happen?
the data must first be ported to a data warehouse or data mart
140
data warehouse
A set of databases designed to support decision-making in an organization
141
data mart
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).
142
online analytical processing (OLAP)
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.
OLAP tools can present results through multidimensional graphs, or via spreadsheet-style cross-tab reports.
143
data cube
A special database used to store data in OLAP reporting.
144
data lake
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.
145
data swamp
An unusable pile of Big Data
146
Hadoop
A set of mostly open source tools to manage massive amounts of unstructured data for storage, extraction, and computation.
Cloudera
147
data cloud
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 be disbanded when it is no longer needed.
Snowflake is the best known of the many firms providing services in this space.
148
what are the four primary advantages of using Big Data technologies in a data cloud
Flexibility: Data lakes can absorb any type of data, structured or not, from any type of source
Scalability: Depending on the solution, a cloud provider may be able to mask the complexity required to scale systems and simply “spin up” resources whenever more capacity is needed
Cost-Effectiveness: much of it open source and that can be started on limited computing resources before scaling, is often considered cheap by data-warehousing standards
Fault Tolerance: Big Data storage is designed in such a way so that there will be no single point of failure. The system will continue to work, relying on the remaining hardware
149
what does ETL mean?
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.
150
the unstructured nature of Big Data tools makes them a logical choice for e-discovery, what does e-discovery mean?
The process of identifying and retrieving relevant electronic information to support litigation efforts.
151
query tools
Tools to interrogate a data source or multiple sources and return a subset of data, possibly summarized, based on a set of criteria.
can access data from multiple lists/databases
152
Python
A general purpose programming language that is also popular for data analytics.
153
R
A programming language specifically created for analytics, statistical, and graphical computing.
154
graphical query tools
tools that allow a user to create a query through a point-and-click or drag-and-drop interface, rather than requiring programming knowledge.
155
canned reports
Reports that provide regular summaries of information in a predetermined format
formats can be hard to alter
156
ad hoc reporting tools
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
157
dashboards
A heads-up display of critical indicators that allow managers to get a graphical glance at key performance metrics
158
data visualization
The graphical representation of data and information.
159
generative AI
A type of artificial intelligence whose output is some type of media: e.g., text, images, audio, video.
Results are usually generated based on a prompt, such as typed or spoken text.
This technology “learns” the patterns and structure of data used during training, and can then generate new output based on the characteristics of this input.
Results can often be refined by further prompt entry
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omnichannel
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.
161
data mining
The process of using computers to identify hidden patterns in, and to build models from, large datasets
162
for data mining to work, 2 critical conditions need to be present, what are they?
1. Organization must have clean & consistent data
2. Events in that data should reflect current & future trends
163
over-engineer
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.
164
what 3 skills does a data mining and business analytics team need?
1. Info Tech ((for understanding how to pull together data, and for selecting analysis tools)
2. Statistics (for building models and interpreting the strength and validity of results)
3. Business knowledge (for helping set system goals and requirements, and offering deeper insight into what the data really says about the firm’s operating environment)
165
when can models yield bad results?
Models influenced by bad data, missing or incomplete historical data, and over-engineering are prone to yield bad results
166
business are using data mining to address issues in...
Customer segmentation—figuring out which customers are likely to be the most valuable to a firm.
Marketing and promotion targeting—identifying which customers will respond to which offers at which price at what time.
Market basket analysis—determining which products customers buy together, and how an organization can use this information to cross-sell more products or services.
Collaborative filtering—personalizing an individual customer’s experience based on the trends and preferences identified across similar customers.
Customer churn—determining which customers are likely to leave, and what tactics can help the firm avoid unwanted defections.
Fraud detection—uncovering patterns consistent with criminal activity.
Financial modeling—building trading systems to capitalize on historical trends.
Hiring and promotion—identifying characteristics consistent with employee success in the firm’s various roles.
167
what is Walmart's key source of competitive advantage
scale
168
The Walmart data/efficiency dance starts with a proprietary and continually refined system called Retail Link. What is that?
Each time an item is scanned by a Walmart cash register, Retail Link not only records the sale, but also automatically triggers inventory reordering, scheduling, and delivery.
This process keeps shelves stocked while keeping inventories at a minimum.
169
how does Walmart keep its extremely accurate inventory?
Requiring suppliers to ship products with RFID tags
speed reordering to avoid stockouts
allow customers placing online orders to pick up items in stores
“Buy Online, Pickup In Store” is one of the differentiators Walmart has over Amazon, and a trip to Walmart to pick up an order is likely to also result in additional purchases, including groceries and other weekly staples.
170
Walmart's Data Cafe
state-of-the-art analytics center at headquarters that leverages an industry-leading data trove that tops forty petabytes
The system provides managers with a central clearinghouse where they can seek help on data-driven problem solving, and the system provides managers with alerts, prompting them to reach out to the Data Café for help in identifying and solving the problem
171
how does walmart use data to gain efficiency?
Walmart uses point-of-sale data, shared via Retail Link, to forecast demand, optimize delivery schedules, and reduce inventory costs
172
What strategy has Walmart used to partner more closely with suppliers?
Walmart demands data sharing, requiring suppliers to manage their own inventory in Walmart warehouses.
173
How has technology helped Walmart maintain low prices?
Technology enables Walmart to track product movement, coordinate with suppliers, and cut costs, passing the savings to customers.
174
why does Walmart need to find huge markets or dramatic cost savings?
Despite its success, Walmart is a mature business that needs to find huge markets or dramatic cost savings to boost profits and continue to move its stock price higher
175
What limitation did Walmart’s data assets have?
The firm’s data assets could not predict impactful industry trends such as the rise of Target and other upscale discounters.
176
What international market is Walmart betting on to beat Amazon?
Walmart sees India as a market where it can beat Amazon.
177
What are some new technologies Walmart is innovating with?
The firm continues to innovate with all sorts of new technologies, including VR for human resources, robotics throughout its supply chain, and self-checkout technologies.
178
With the U.S. market near saturation, where is Walmart looking for new growth?
While Walmart’s U.S. market is near saturation, the firm is looking abroad, especially to India, for new growth.
179
After decades where AI was initially promised but not delivered (often referred to as “the AI winter", what is the AI winter?
a period of reduced interest in and funding for AI projects.
This resulted from a failure of AI to deliver on much-hyped initial promises.
Advances in fast/cheap processor and storage technology, cloud computing and access to tremendous amounts of parallel computing, high-speed broadband, and the massive amount of input data from the Internet and other sources has enabled several advances in AI during the past decade, plus.
The advance of generative AI have further pushed interest in AI to an all-time high in terms of investment and use.
180
the goal of AI
to create computer programs that are able to mimic or improve upon functions that would otherwise require human intelligence
181
GenAI results are guided by user inputs, known as prompts which are
requests made to generative artificial intelligence systems
182
AI hallucination
In the context of AI, hallucination refers to answers that are generated results that are incorrect and aren't based on facts.
Some refer to AI hallucination as “made up” answers. AI hallucinates not because it is sinister or it's trying to lie, but because systems struggle to find a set of related terms and concepts.
The AI strings together a set of words that are a best match mathematically, but that don’t result in facts.
183
what's the difference between ChatGPT & GPT?
ChatGPT is the name of the chatbot that consumers access, while GPT itself is the foundation model used to build the tool that delivers these results.
And Open AI’s GPT foundation model is being used to power other products.
184
Did OpenAI invent GenAI?
OpenAI didn’t invent GenAI, nor many of the key technologies that make it possible;
however, the firm’s ChatGPT-3.5 was a significant advance in GenAI and was the most robust GenAI ever made publicly accessible and free for trial over the Internet.
ChatGPT-3.5 could pass exams, synthesize and summarize text, and even compose novel, stylistically accurate results (e.g., create a poem, explain a concept using language that a typical middle-schooler would understand).
185
for genAI like ChatGPT to "understand" texts for input and output, it uses a subset category of AI referred to as what?
large language models (LLMs)
186
how are LLMs created?
1. foundation model is built (breaks apart text & creates multi-tiered relationships betw individual elements of text)
2. foundation GPT model is fed a lot of data to idenfify these relationships and come up with a trained LLM (users interact with trained LLMs -- ChatGPT)
3. trained model LLM (This LLM already understands how to break apart language, how to weigh relationships it identifies, and how to come up with a complex, multifaceted, nuanced response that can consider words, context, style, and more)
187
During training, models create what AI engineers refer to as parameters. What are those?
Values that are created by the foundation model and that are used by LLMs to determine text elements, relationships between these elements, and that are further refined during training.
The more parameters that are in a model, the more complex and comprehensive the resulting LLM will be.
188
corpus
In AI, this refers to the data used to train a model before it can be used.
a model's abilities are limited by the corpus on which it was trained
189
neural networks
are statistical techniques used to hunt down and expose patterns. Neural networks identify patterns by testing multilayered relationships that humans can’t detect on their own.
Many refer to the multilayered interconnections among data as mimicking the neurons of the brain (hence the name).
If a set of interrelationships is strong, they go into the pattern-matching scheme. If a better set of relationships is found, old ones are tweaked or discarded.
Neural networks are often referred to as a “black box,” meaning that the weights and relationships of data that identify patterns approximate a mathematical function, but are difficult to break out as you would in a traditional mathematical formula.
You’ll often see neural networks used as the technology that enables specific categories of AI use, such as image recognition or large language models.
190
deep learning
a type of machine learning that uses multiple layers of interconnections among data to identify patterns and improve predicted results
Some technologists refer to “deep” as having more than one “hidden” layer between input and output. That might not mean much to most managers, but just as “Big Data” is “a lot,” “deep learning” has more analytical complexity.
Some firms are able to see a tremendous jump in model accuracy when moving from standard one-layer machine learning to deep learning.
For example, when Amazon shifted to deep learning in its forecasting models it saw a fifteen-fold improvement in model accuracy—results that allowed it to roll out Amazon Prime One Day Delivery in more markets, since smaller warehouses would be more accurately and more cost-effectively stocked with goods consumers would most likely order.
191
large language model (LLM)
a type of neural network AI uses for language understanding and generation. LLMs form the basis of most generative AI, since a prompt entry by a user must be interpreted, and text-based results need to be generated.
192
Using an LLM to interpret language can also be referred to as
natural language processing, or NLP
193
foundation model
the model or base technology used to train a large language model.
In the example of ChatGPT-3, OpenAI's GPT-3 is the base model that is used to train the LLM that users eventually use to ask and answer questions.
194
prompt engineering
a fancy way of saying “learning how to talk to AI to get desired results.”
Most generative AI systems come with documentation that can help you improve prompt engineering so that you can use systems better and more efficiently.
Many GenAI systems also allow you to refine results through entering additional information through subsequent prompts
195
artificial general intelligence (AGI)
refers to software that’s capable of learning and reasoning on any task or subject, including developing reasoning about topics not presented through a training corpus.
Most experts agree we have not yet achieved artificial general intelligence with current AI systems.
While some researchers suspect we may never achieve this goal, creating AGI is a stated goal of several organizations, including OpenAI.
196
turing test
a test of a computer’s ability to exhibit behavior so that it is indistinguishable from a human.
The term is often used and it’s hotly debated as to whether or not chatbots using large LLMs have passed the Turing test, and whether the Turing test is even a relevant way to think about advanced AI capabilities
197
expert systems
AI systems that leverage a set of programmed decision rules or example outcomes to perform a task in a way that mimics applied human expertise.
Expert systems are used in tasks ranging from medical diagnoses to product configuration.
expert systems don't need massive amounts of data to set up
however, they do require the ability to extract rules or expertise, which often involves the time and expense of working with domain experts, building systems, and thorough testing and iteration to ensure outcomes are what is expected
198
genetic algorithms
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.
use massive amounts of data to identify patterns in the data and come up with weights between identified patterns in order produce accurate results
Genetic algorithms have been used for a wide variety of applications, including designing superior financial models, improving satellite deployment for global coverage, designing earthquake-resistant transport systems, suggesting the most efficient layout for solar arrays, and solving traffic congestion problems
199
supervised learning
A type of machine learning where algorithms are trained by providing explicit examples of results sought, like defective versus error-free, or stock price.
200
self-supervised learning
Sometimes called unsupervised learning, where systems build pattern-recognizing algorithms using data that has not been pre-classified.
Some form of self-supervised learning is usually used to train LLMs, like OpenAI's GPT models, and researchers at Google used self-supervised learning in a robot that “taught” itself to walk.
201
semi-supervised learning
machine learning where data used to build models that determine an end result may contain data that has explicitly labeled outputs but is also free to develop and use its own additional classifications that may further enhance result accuracy
(e.g., “hey software, take a look at my categorizations and see if they are valid or if you can come up with better or missing ones”)
202
While firms use self-supervised learning to begin work on LLMs, many firms (including OpenAI with ChatGPT) use humans to examine an AI's results and provide correction. This technique is called RLHF which is
reinforcement learning from human feedback
RLHF leverages input from human evaluators who provide feedback and ratings to continually tune results during AI training.
Models are typically encouraged by some sort of reward function, and human input guides training to favor certain outcomes and avoid others.
RLHF isn’t perfect or all-knowing so it can’t possibly pre-screen for all troubling issues, but it can help provide guidance in ambiguous situations, and help minimize results that are incorrect, harmful, untruthful, or biased.
It also can be difficult to responsibly execute, as many workers involved in these efforts cite PTSD-like conditions from being immersed in results combining the most vile elements of the Internet.
203
constitutional AI
A method for providing alignment and safety in an AI by incorporating a set of specific rules or guidelines that an AI must follow as machine learning takes place.
Anthropic
204
What does ChatGPT stand for
generative pre-trained transformer
205
Why is the T in chatGPT important?
t for transformer
The Transformer’s giant leap forward is that the technology allowed all words in a given body of text to be analyzed in parallel rather than sequentially.
Transformers let generative AI consider lots of relationships (words, concepts, style, context) together.
Transformers also allow models to be trained far quicker on a much larger amount of data, and to generate results that consider complex relationships much more quickly.
The important pieces of text are identified as worthy of attention (hence the paper’s name). The AI concept of attention was identified by earlier researchers, but it’s the Transformer that lets GPT and other GenAI produce sophisticated, human-like answers that go beyond the simple trick of auto-complete.
206
why should users of genAI be cautious?
nswers can often be wrong, they may be offensive, and there are a host of additional issues to worry about, including whether incorporating a firm's proprietary information into a tool puts the firm at security, privacy, or regulatory risk, or if results generated by AI violate copyright
207
Gen AI will be used to enhance work by
systhesis and summary
creative work and brainstorming
education, training, and quality improvement
208
pair programming
A software development technique where two programmers work side-by-side, looking at the same screen, sharing their collective insights to write, test, and debug code.
BEFORE GENAI
209
Microsoft-owned GitHub launched its own Copilot program to act as its real-time code assistant with new coding language support rolling out regularly
programmers are leveraging tools like GitHub Copilot to improve the code they write, to debug and document code, and to learn quickly about new concepts and tech offerings.
The rise of these tools has had such strong product–market fit that the go-to sight for programming questions, StackOverflow, has seen a precipitous drop in usage.
210
CAPTCHAs (completely automated public Turing test to tell computers and humans apart)
meant to keep out automated software that may create accounts used in spamming or other nefarious activity
Google’s widely used method, known as reCAPTCHA, has asked users to prove their superior-to-robot chops by classifying images, such as hard-to-read letters or house numbers, and to identify squares containing stoplights and traffic signs.
If you’ve taken part, you were contributing to massive databases that are used to help software “learn” by recognizing human-classified images (data that is used in various forms of supervised learning model building).
211
OCR algorithms
Optical Character Recognition.
Software that can scan images and identify text within them.
212
what's happening in graphic arts with GenAI?
In graphic arts, Canva has incorporated GenAI tools from various vendors, while Adobe has built its own proprietary tools and has trained its GenAI on images that are either have no copyright or that Adobe has secured the rights to.
This latter approach may ease firms concerned that GenAI might create images that violate intellectual property of rights holders. It will also enable Adobe to bypass licensing fees that a firm using third-party tools need to pay.
213
godfather of modern AI
Geoffrey Hinton
quit his engineering leadership role at Google and went public with fears about the technology
214
AI Security risks
An AI can memorize sensitive data and inadvertently leak or expose the data to others, opening a firm to significant business and legal risk.
Firms warning employees not to share corporate secrets or private information with GenAI include Walmart, and even cloud providers Amazon and Microsoft.
Firms using systems that allow for more secure creation of AI that lives within firm walls also need to consider if these custom AI need to be further walled off because only certain workers should have access to proprietary data and insight.
The creation of such systems is also a security risk if a new set of unsecure or unmonitored data lingers as a site for hackers and data thieves.
215
prompt-injection
Compromising generative AI by entering prompts that cause it to behave in unintended ways.
Examples might have an AI bypass existing security concerns, release proprietary data, or issue a prompt in advance of another user's engagement that would distort results from subsequent use.
216
data poisoning
Deliberately feeding incorrect data to an AI so that it generates incorrect results.
217
deepfakes
Sophisticated media (audio, image, video) created by AI that attempts to look or sound like a real person or event.
218
seed round
The initial round of capital provided to a startup, often by angel investors or venture firms focused on early-stage investments.
If the firm is successful, the seed round is usually followed, when particular milestones are achieved, by subsequent and larger rounds of investment, typically labeled alphabetically (e.g., series A, series B, etc.).
219
diversity & bias in AI
Many types of AI have been shown to provide biased results—including those that negatively influence women and minorities.
Much of this is the result of systems that are, themselves, trained using biased data.
A lack of diversity on design, programming, and testing teams can also lead to the development and release of biased systems.
Such can not only harm individuals impacted by biased systems, but can also harm firm reputation and put the company at legal risk.
But addressing these issues is also challenging.
Results in one market might not reflect the demographics of a client base in another market.
Results using past demographic data might not reflect the demographics when systems are rolled out.
220
Neural network models are said to operate in a “black box.” Why is this bad?
These models might violate legislation that requires demonstrable results in decision making in some legal areas, such as loan granting in a way that proves discrimination did not occur.
221
change management
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.
222
technical, organizational, legal and societal challenges of AI & ML
data quality (inconsistent or unintegratable data)
data security (firms using customer data or datasets with offensive or risky data is bad for firm)
not enough data (inability to predict black swan events
change management
223
How can we make more ethical and less risk-prone systems
hire diversely
hire ethicists
develop a code of tech ethics
create a systems review board
create and enforce tech audit trails
partner to build better tech
develop and refine clear employee policies
implement strong tech and procedural training programs
gather and act on input regarding flaws
provide a means for remediation
test and audit -- Red Teaming
roll out tech gradually
224
audit trails
An audit trail exposes how and when information systems are used so that the way a firm arrived at a particular outcome can be identified.
Audit trails can also ensure that triggers are in place to identify problems and prevent common issues that may include illegal data access and unsafe data exposure to existing staff, contractors, or external parties.
225
red teaming
where a group unaffiliated with developers deliberately tries to undermine safety procedures in a system, hack the technology, and raise any additional concerns that should be addressed before deployment
226
ITIL
IT Infrastructure Library, which covers best practices for delivering IT services.
227
COBIT
(Control Objectives for Information and Related Technologies)
A continually-evolving best-practices framework for IT governance that includes guidance on implementation, monitoring, and improving IT systems and organizations.
228
how did Spotify gain AI skills through their acquisition of the Echo Nest?
pay attention to what the world is saying about music. The firm’s software constantly scours the Web, “reading” music blogs, news reports, and more
Using The Echo Nest, Spotify is helping to curate the cloud according to your taste. Spotify’s “Discover Weekly” is essentially a custom-built “station for you” created by examining your playlists, your listening habits, and what it learns about its millions of other users.
And the firm hasn’t stopped with Echo Nest. Subsequent acquisitions have fueled the firm’s skill in APIs, machine learning, audio detection, and television recommendation.
The firm even bought a blockchain company to help artists and labels with licensing and copyright issues. Spotify is also a brilliant user of social media. The user-specific release of “Spotify Wrapped” has become a holiday gift to fans that’s also a viral sensation.
Discover Weekly uses AI to understand your listening habits and make recommendations for new music based on how you are clustered, collaborative-filtering-style.
229
name the different layers in the hardware/software layer cake from top to bottom
user programs
- user interface
- system calls
- program control, I/o, file systems,
comms, error mngt, resource,
auditing, security
hardware
- = part of operating system
230
why are packaged enterprise systems great?
can streamline processes
make data more usable
ease the linking of systems with software across the firm with key business partners
makes firms more attractive acquisition targets
systems that work smoothly internally may find it easier to partner with others
231
Since many firms have _____ procedures for accounting, finance, inventory management, and human resource functions, it often makes sense to buy a _____ ______ to support some of these functions.
similar, software package
232
For many firms, installing and deploying enterprise systems have been ____, with some firms experiencing ____ or even _____ from botched efforts
difficult, loss, bankruptcy
233
Most enterprise software works in conjunction with a ___ ____ ___, which stores and retrieves the data that an application creates and uses.
database management system (DBMS)
234
why is the software business attractive?
near-zero marginal costs
opportunity to establish a standard
(creating competitive advantages of network effects and switching costs)
235
are the majority of people who work on open source projects paid by commercially motivated employers?
yes
236
what is a primary advantage of adopting OSS?
the ability to free up time-constrained and difficult-to-hire technical staff to focus on value added products
237
does OSS have fewer/more bugs than its commercial counterparts?
fewer bugs due to the large number of software developers who have looked at the code
238
does every commercial product have an open source equivalent?
just about every type of commercial product HAS an open source equivalent
239
why might a software developer choose to operate as Saas providers as opposed to in a packaged software company like SAP?
while a packaged software company like SAP must support MULTIPLE versions of its software to accomodate operating systems like Windows, and Linux, etc, a Saas provider develops, tests, deploys, and supports just ONE version of the software executing on its own servers
240
does virtualization work on the desktop?
virtualization also works on the desktop, allowing multiple operating systems (Mac OS, Linux, Windows) to run simultaneously on the same platform
241
what are some benefits apps have over packaged software and browser-based alternatives?
always open
distributed at a fraction of the cost of conventional packaged software
richer more interactive interface options
most smartphones allow apps to integrate with the OS
can lock user into a given platform
many products upgrade apps in the background so users have latest features and no bugs (low software maintenance cost)
several businesses wouldn't exist without their apps (Uber, Instagram & Whatsapp)
242
what are critics saying about apps
some say apps force consumers into smartphone-walled gardens and raise consumer-switching costs
more challenging updates
version control
A/B testing is a lot harder when compared to browser-based applications
app discovery is hard & generating that consumer awareness among the growing crowd of app offerings
243
unlike physical products assembled from raw materials, the marginal cost to produce an additional copy of a software product is _____.
effectively zero
244
with platform as a service (PaaS), the vendor supplies the support software and operating system, but the client does what?
writes their own code
245
How are the costs associated with SaaS treated?
the associated costs are treated as variable operating expenses rather than fixed capital expenses
246
SaaS means a greater consumerization of technology, which is rarely, if ever, works out well for firms
TRUE or FALSE?
False
The consumerization of corporate technology isn’t all bad. Employee creativity can blossom with increased access to new technologies, costs might be lower than home grown solutions, and staff could introduce the firm to new tools that might not otherwise be on the radar of the firm’s IS Department.
247
when complex legacy systems have to be ported, companies may find it hard or impossible to do what?
to move to cloud computing
this is bc most cloud computing efforts focus on new software development projects rather than options for old software
248
a server running ____ software can create smaller compartments in memory that each behave as a separate computer with its own operating system and resources
virtualization
249
when a firm runs an instance of a PC's software on another machine and simply delivers the image of what's executing to the remote device, it is said to be operating on a(n) ____.
virtual desktop
250
what is not an option for firms relying on unique processes, procedures, or technologies that create vital, differentiating competitive advantage?
purchasing package software from a vendor to automate such efforts
251
what can help a firm deal with the spiking impact from black swan events?
scalable computing resources
252
Google, Sun, Microsoft, IBM, and HPE have all developed what?
rapid-deployment server farm modules
253
when is dynamic pricing tricky
where consumers make repeated purchases and are more likely to remember past prices, and when they have alternative choices
grocery stores or department stores
254
the phrases table, column, and row are also referred to by the names __________ respectively
file, field, record
255
____ systems are often used to empower employees to track and record data at nearly every point of customer contact
CRM systems (customer relationship management)
256
setting up new collection efforts, surveys, or systems to obtain data is called _____?
data sourcing
257
what are the 3 "Vs" of Big Data?
volume
velocity
variety
258
the ______ breed of cloud-based data tools is specifically designed to gather data from disparate sources and turn them into standard formats that can be interrogated by managers
snowflake
259
systems that can absorb any type of data, structured or not, from any type of source are often referred to as:
schema-less
260
an integrated shopping experience and unified customer view across channels is sometimes referred to as _____.
omnichannel
261
personalizing an individual customer's experience based on the trends and preferences identified across similar customers
collaborative filtering
262
what does walmart use to sift thru social media posts about the firm?
Hadoop
263
why did walmart stop sharing its data assets with information brokers like ACNielsen and Information Resources?
due to walmart's huge scale, the agencies offered no extra value with their additional data
264
using prompts, ____ learns the data, and generates output (typically some type of media) based on the information gathered from the prompts
generative AI
265
artificial intelligence doesn't use _____ but uses computer software to improve products and functions.
human intelligence
266
anthropic uses constitutional AI to build what it considers:
a more ethical AI
267
goldman sachs, a financial firm, has predicted that AI could replace up to 44% percent of work done in the ____ field.
legal
268
many AI companies are facing ____ over how they are training their AI engines
copyright lawsuits
269
the very beginnings of AI, the foundation models that have to be trained are the
naked algorithms
270
firms can take a number of steps to set their AI engines up for success including hiring diversely, adding ethicists to the team and creating
a system review board
271
field that will uniquely identify each row in the table
primary key
272
connection between 2 tables, many cases when the data in one table can be related to the data in another table
relation
273
2 types of TPS
on-line mode: could be real line
batch mode: done after hours (get a list of all sales in one day)
274
system that provides rewards in exchange for consumers, allowing for tracking and recording of their activities
loyalty card
275
what are the basic components (3 layers) of a data warehouse
top: front end client (presents results thru reporting, analysis, and data mining tools
middle: analytics engine (used to access and analyze the data)
bottom: database server (data is loaded and stored)
276
properties of data mining
automatic discovery of patterns
prediction of likely outcomes
creation of actionable information
focus on large data sets and databases
277
key components of a neural network (3)
input layer: receives raw data (ex; text, images & numbers)
hidden layers: perform computations and pattern recognition, each neuron in a layer connects to neurons in the next layer, applying weights and biases to data, activation functions decide whether to pass the information forward
output layer: produces the result, such as a prediction, classification, or decision
