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IT > Unit 2 EXAM HOLIDAYS GLOSS TERMS+ EXAM > Flashcards

Unit 2 EXAM HOLIDAYS GLOSS TERMS+ EXAM Flashcards

1
Q

“APA referencing”

A

“A citation style used for academic and research papers, following the guidelines of the American Psychological Association.”

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2
Q

“Archiving”

A

“The process of storing data that is no longer actively used but must be kept for future reference or compliance.”

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3
Q

“Back up”:

A

“Creating copies of data to protect against loss or damage, ensuring it can be restored if needed.”

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4
Q

“Capabilities of software”:

A

The functionalities and tasks that software is able to perform, such as data processing or report generation.”,

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5
Q

Consequences for organizations that fail or violate security measures”:

A

“Potential penalties, including legal actions, financial loss, and damage to reputation, for not adequately securing data.”,

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6
Q

“Characteristics of information for educating targeted audiences”:

A

“Key attributes such as clarity, relevance, and accessibility to ensure that the information effectively communicates with the audience.”,

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7
Q

“Cloud computing”:

A

“Utilizing remote servers hosted on the internet for data storage, management, and processing instead of local systems.”

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8
Q

“Computational thinking”:

A

“A problem-solving process that involves breaking down tasks, identifying patterns, and creating algorithms to tackle complex issues.”,

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9
Q

“Conventions”

A

“Agreements or guidelines that ensure consistency and clarity, such as naming conventions in software development or email formatting rules.”

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10
Q

“Criteria evaluate the effectiveness of current data and information security strategies”

A

Standards used to assess how well security strategies protect data from threats and unauthorized access.”

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11
Q

“Critical Path”

A

“The sequence of tasks in a project that determine the minimum time needed to complete the project.”

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12
Q

“Cybersecurity”:

A

“The practice of protecting systems, networks, and programs from digital attacks or unauthorized access.”

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13
Q

“Data”:

A

“Raw facts and statistics collected for reference or analysis.”

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14
Q

“Database structures”:

A

“Organized collections of data stored electronically, typically using tables, fields, and relationships.”,

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15
Q

“Data analytics”:

A

“The process of analyzing raw data to uncover patterns, trends, and insights.”,

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16
Q

“Data structures”:

A

“The organization of data for efficient access and modification, such as arrays, lists, or trees.”,

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17
Q

“Data types”:

A

Categories of data that determine how the data is used, including integer, string, boolean, etc.”,

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18
Q

“Design principles”:

A

Fundamental guidelines for creating effective and aesthetically pleasing systems or solutions.”

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19
Q

Design Idea tools”

A

Techniques or software used to conceptualize and visualize design ideas, such as wireframes or sketches.”,

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20
Q

Design Tools”:

A

Software or methods used to create designs, such as Adobe Photoshop or wireframing tools.”,

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21
Q

“Dependency”:

A

“A relationship between tasks where one task relies on the completion of another before it can start.”,

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22
Q

Design thinking”:

A

“A problem-solving approach centered around empathy, ideation, prototyping, and iterative testing.”,

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23
Q

“Digital system”:

A

“A system that processes digital data, such as computers, smartphones, or embedded systems.”,

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24
Q

“Disaster Recovery Plan”:

A

A set of procedures to restore critical IT functions and data after a disaster or system failure.”,

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25
Q

“Dynamic Data Visualization”:

A

“Interactive visual representations of data that can change based on user interaction or real-time data.”,

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26
Q

Effectiveness – Solution”:

A

How well a solution achieves the intended objectives or meets the user’s needs.”,

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27
Q

Disposing of files”:

A

“The secure destruction or deletion of data that is no longer needed, preventing unauthorized access.”,

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28
Q

Effectiveness – Information Management Strategy”:

A

“How well a strategy organizes, stores, and retrieves information to meet organizational goals.”,

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29
Q

“Effectiveness - Networks”:

A

“How efficiently and reliably a network allows communication between devices and systems.”,

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30
Q

“Efficiency”:

A

“The ability to achieve a goal with minimal time, effort, and cost.”,

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31
Q

“Efficiency – Solution”:

A

“How resource-efficient a solution is in terms of time, effort, and cost to achieve its objectives.”,

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32
Q

“Efficiency – Networks”:

A

How well a network minimizes delays and maximizes data transfer speeds.”,

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33
Q

“Ethical issues”:

A

“Moral challenges related to data usage, including privacy, consent, and fairness.”,

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34
Q

Evaluation Criteria – Design ideas”:

A

“The standards used to judge the feasibility, innovation, and relevance of design ideas.”,

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35
Q

“Evaluation Criteria - Designs”:

A

“Measures used to assess the effectiveness, usability, and visual appeal of designs.”,

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36
Q

Evaluation Criteria - Software”:

A

“Benchmarks for assessing the functionality, reliability, and user-friendliness of software.”,

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37
Q

“Evaluation Strategies”:

A

“Approaches used to assess the performance, quality, and effectiveness of solutions.”,

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38
Q

“Features of a research question”:

A

“A well-defined, clear, and answerable question that guides research and analysis.”,

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39
Q

“Foreign Key”:

A

“A field in one table that links to the primary key of another table to create relationships between the tables.”,

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40
Q

“File Management”:

A

“The process of organizing, storing, and retrieving files for efficient access.”,

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41
Q

“Format”:

A

“The physical layout or presentation of data, such as text, images, tables, or graphs.”,

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42
Q

“Functions and Techniques – spreadsheets”:

A

“Methods for organizing and analyzing data in spreadsheets, such as using formulas and functions like SUM or VLOOKUP.”,

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43
Q

“Functions and Techniques – databases”:

A

“Operations such as querying and managing databases, often using SQL.”,

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44
Q

“Functions and Techniques – data visualizations”:

A

“The use of graphical representations like charts, graphs, or dashboards to present data.”,

45
Q

“Hardware”:

A

“The physical components of a computer or digital system, such as processors, storage devices, and network equipment.”,

46
Q

“Infographics”:

A

“Visual representations designed to simplify and present complex information clearly.”,

47
Q

“Information system”:

A

“An integrated set of components used to collect, process, store, and disseminate information.”,

48
Q

“Information”:

A

Data that has been processed and organized to be meaningful and useful.”,

49
Q

“Integrity of Data”:

A

“The accuracy, consistency, and reliability of data over its lifecycle.”,

50
Q

“Internet of Things (IoT)”:

A

“A network of physical devices connected to the internet that collect and share data.”,

51
Q

“Legal requirements (including acts)”:

A

“Laws and regulations that govern data protection, security, and usage.”,

52
Q

“Managing files”:

A

“The practice of organizing and controlling files to ensure accessibility and security.”,

53
Q

“Milestone”:

A

“A significant event or checkpoint in a project timeline.”,

54
Q

“Naming conventions”:

A

“Agreed-upon rules for naming files, variables, or objects to maintain consistency.”,

55
Q

“Networks - wired”:

A

“Networks that use physical cables, such as Ethernet, to connect devices.”,

56
Q

“Networks - wireless”:

A

“Networks that use radio waves, like Wi-Fi, to connect devices without cables.”,

57
Q

“Networks - mobile”:

A

“Networks that use cellular technology, such as 4G or 5G, to connect mobile devices to the internet.”,

58
Q

“Network attached storage”:

A

“A storage device connected to a network, allowing multiple devices to access it.”,

59
Q

“Network hardware”:

A

“The physical components needed to establish and maintain a network, such as routers, switches, and cabling.”,

60
Q

“Physical security controls”:

A

Security measures that protect physical assets, such as locks, surveillance cameras, or access controls.”,

61
Q

“Predecessor”:

A

A task that must be completed before another can begin in a project timeline.”,

62
Q

“Primary Data”:

A

“Data collected firsthand through methods like surveys, interviews, or direct observation.”,

63
Q

“Primary Key”:

A

“A unique identifier for each record in a database table, ensuring no duplicates exist.”,

64
Q

“Processing features”:

A

“Capabilities of a system or software to manipulate or transform data.”,

65
Q

“Project management”:

A

“The process of planning, executing, and controlling a project to meet objectives within time and budget constraints.”,

66
Q

“Pseudocode”:

A

“A simplified, human-readable version of programming logic used to design algorithms.”,

67
Q

“Quantitative Data”:

A

“Measurable data that can be expressed in numerical terms, such as statistics or metrics.”,

68
Q

“Qualitative Data”:

A

“Descriptive data that captures qualities or characteristics and is not easily measurable in numbers.”,

69
Q

“Relational Databases”:

A

Databases structured to recognize relationships between tables, using primary and foreign keys.”,

70
Q

“Secondary Data”:

A

“Data that has been collected by someone else, such as reports, articles, or government statistics.”,

71
Q

“Security Protocols”:

A

“Rules and procedures for securing communication and data transfer over networks.”,

72
Q

“Security threats”:

A

“Potential dangers to data security, such as malware, phishing, or hacking.”,

73
Q

“Software”:

A

“Programs and applications that perform tasks on digital systems.”,

74
Q

“Software requirements specification (SRS)”:

A

“A document detailing the functions, features, and constraints of a software product.”,

75
Q

“Software security controls – Software”:

A

“Security measures within software, such as encryption or authentication, to protect data and systems.”,

76
Q

“Solution (digital)”:

A

“A digital tool or system designed to solve a specific problem.”,

77
Q

“Solution Constraints”:

A

“Limitations or restrictions in a solution, such as budget, time, or resources.”,

78
Q

“Solution Requirements”:

A

“The features and functionalities a solution must include to meet user needs.”,

79
Q

“Solution Scope”:

A

“The boundaries and extent of what a solution will achieve.”,

"Systems thinking": "An analytical approach that considers the interrelated components of a system and how they influence each other.",
80
Q

“Table Normalization”:

A

“A process in database design to organize tables to reduce redundancy and dependency.”,

81
Q

“Techniques for coding data”:

A

“Methods for structuring and organizing data for analysis or storage.”,

82
Q

“Testing techniques”:

A

“Methods used to ensure a solution or system works as expected, such as unit testing or system testing.”,

83
Q

“Threats - accidental”:

A

“Unintentional actions or events that risk data, such as human error.

84
Q

what is field type “ text “ used for?

A

Used for alphanumeric data, such as names, addresses, or international phone numbers.

85
Q

what is field type “ numeric “ used for?

A

For numerical values where calculations are required (e.g., postcodes, tax file numbers).

86
Q

what is field type “ character “ used for?

A

Single characters or special symbols, often used in coding or database fields.

87
Q

what is field type “ float “ used for?

A

Decimal numbers used in calculations that require precision.

88
Q

Existence Check

A

Ensures required fields are filled out to avoid incomplete data entries.

89
Q

Type Check

A

Confirms that the correct type of data (e.g., numbers, text) is entered into the corresponding field. Example (e.g., numeric data in a numeric field).

90
Q

Range Check

A

Validates that the entered data falls within a specified range (e.g., dates within a valid period). Example (e.g., a score between 0 and 100).

91
Q

SUM():

A

Adds a range of cells together. Example: “=SUM(A1:A10)” calculates the total of values in cells A1 through A10.

92
Q

AVERAGE():

A

Calculates the mean of a range of cells. Example: “=AVERAGE(B1:B10)” gives the average value in cells B1 through B10.

93
Q
  • IF():
A

Conditional function that returns one value if a condition is true and another if it is false. Example: “=IF(C1>70, “Pass”, “Fail”)” returns “Pass” if the value in C1 is greater than 70, otherwise “Fail”.

94
Q

Data Validation

A

Prevents incorrect data entry by restricting the type of data that can be input into a cell. For instance, restricting a cell to accept only dates between 01/01/2020 and 12/31/2020.

95
Q

Conditional Formatting:

A

Changes the appearance of cells based on their values. For example, highlighting cells in red where values are below a certain threshold.

96
Q

Purpose id data visualisation:

A

The main goal of data visualization is to present data in a clear and concise way that allows for easy interpretation. This includes identifying trends, comparing data, and illustrating relationships.

97
Q

Types of data visualisation:

A

Common types include bar charts, line graphs, pie charts, scatter plots, and heat maps. Each type is suited to different kinds of data and analysis needs.

98
Q

Clarity- data visualisation

A

Visualisation should be easy to read and interpret, avoiding clutter or unnecessary elements.

99
Q

Accuracy-data visualisation

A

Data should be represented faithfully, without distortion or misrepresentation. For example, starting a bar chart at zero to avoid exaggerating differences.

100
Q

Aesthetics-data visualisation

A

Use of color, layout, and design should enhance the understanding of the data, not distract from it.

101
Q

Guidelines for Creating Effective Charts:

A
  • Use of Legends: Clearly label data series in charts to prevent confusion. Legends should be easy to understand and should not obscure the data.
  • Appropriate Colors: Use colours that are distinct and appropriate for the type of data. Avoid colours that are too similar or hard to distinguish.
  • Providing Context: Include historical data or benchmarks to give context to the current data. This helps in understanding trends and making comparisons.
102
Q

Efficient Data Collection Techniques:

A
  1. Clear: Data collection methods should be easy to understand and implement.
  2. Accurate: The data collected should be correct and free from errors.
  3. Low Cost: Data collection should be cost-effective, minimising unnecessary expenses.
  4. Complete: The data collected should cover all necessary aspects to ensure comprehensiveness.
103
Q

Data Alignment and Formatting Techniques

A

Alignment: Adjusts the placement of data within a cell (e.g., left, center, or right alignment).

Indentation: Adds space between the data and the cell border to create a visual hierarchy.

Number Formatting: Adjusts how numbers are displayed (e.g., currency, percentage, or decimal format).

104
Q

AND()- Logical Operators and their Usage

A

Returns TRUE if all conditions are met.

105
Q

OR()- Logical Operators and their Usage

A

Returns TRUE if any one of the conditions is met.

106
Q

NOT()- Logical Operators and their Usage

A

Reverses the result of a condition (i.e., TRUE becomes FALSE and vice versa).

107
Q

Appearance Design Tools:

A

Include IPO (Input-Process-Output) charts, flowcharts, and wireframes to plan the look and feel of the application.

108
Q

Functionality Design Tools:

A

Focus on the system’s operations and include tools like data flow diagrams (DFDs) and entity-relationship diagrams (ERDs).

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