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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
"Dynamic Data Visualization":
"Interactive visual representations of data that can change based on user interaction or real-time data.",
26
Effectiveness – Solution":
How well a solution achieves the intended objectives or meets the user's needs.",
27
Disposing of files":
"The secure destruction or deletion of data that is no longer needed, preventing unauthorized access.",
28
Effectiveness – Information Management Strategy":
"How well a strategy organizes, stores, and retrieves information to meet organizational goals.",
29
"Effectiveness - Networks":
"How efficiently and reliably a network allows communication between devices and systems.",
30
"Efficiency":
"The ability to achieve a goal with minimal time, effort, and cost.",
31
  "Efficiency – Solution":
"How resource-efficient a solution is in terms of time, effort, and cost to achieve its objectives.",
32
"Efficiency – Networks":
How well a network minimizes delays and maximizes data transfer speeds.",
33
"Ethical issues":
"Moral challenges related to data usage, including privacy, consent, and fairness.",
34
Evaluation Criteria – Design ideas":
"The standards used to judge the feasibility, innovation, and relevance of design ideas.",
35
"Evaluation Criteria - Designs":
"Measures used to assess the effectiveness, usability, and visual appeal of designs.",
36
Evaluation Criteria - Software":
"Benchmarks for assessing the functionality, reliability, and user-friendliness of software.",
37
"Evaluation Strategies":
"Approaches used to assess the performance, quality, and effectiveness of solutions.",
38
"Features of a research question":
"A well-defined, clear, and answerable question that guides research and analysis.",
39
"Foreign Key":
"A field in one table that links to the primary key of another table to create relationships between the tables.",
40
"File Management":
"The process of organizing, storing, and retrieving files for efficient access.",
41
"Format":
"The physical layout or presentation of data, such as text, images, tables, or graphs.",
42
"Functions and Techniques – spreadsheets":
"Methods for organizing and analyzing data in spreadsheets, such as using formulas and functions like SUM or VLOOKUP.",
43
"Functions and Techniques – databases":
"Operations such as querying and managing databases, often using SQL.",
44
"Functions and Techniques – data visualizations":
"The use of graphical representations like charts, graphs, or dashboards to present data.",
45
  "Hardware":
"The physical components of a computer or digital system, such as processors, storage devices, and network equipment.",
46
"Infographics":
"Visual representations designed to simplify and present complex information clearly.",
47
"Information system":
"An integrated set of components used to collect, process, store, and disseminate information.",
48
"Information":
Data that has been processed and organized to be meaningful and useful.",
49
"Integrity of Data":
"The accuracy, consistency, and reliability of data over its lifecycle.",
50
  "Internet of Things (IoT)":
"A network of physical devices connected to the internet that collect and share data.",
51
"Legal requirements (including acts)":
"Laws and regulations that govern data protection, security, and usage.",
52
"Managing files":
"The practice of organizing and controlling files to ensure accessibility and security.",
53
"Milestone":
"A significant event or checkpoint in a project timeline.",
54
"Naming conventions":
"Agreed-upon rules for naming files, variables, or objects to maintain consistency.",
55
"Networks - wired":
"Networks that use physical cables, such as Ethernet, to connect devices.",
56
"Networks - wireless":
"Networks that use radio waves, like Wi-Fi, to connect devices without cables.",
57
"Networks - mobile":
"Networks that use cellular technology, such as 4G or 5G, to connect mobile devices to the internet.",
58
"Network attached storage":
"A storage device connected to a network, allowing multiple devices to access it.",
59
"Network hardware":
"The physical components needed to establish and maintain a network, such as routers, switches, and cabling.",
60
"Physical security controls":
Security measures that protect physical assets, such as locks, surveillance cameras, or access controls.",
61
"Predecessor":
A task that must be completed before another can begin in a project timeline.",
62
"Primary Data":
"Data collected firsthand through methods like surveys, interviews, or direct observation.",
63
"Primary Key":
"A unique identifier for each record in a database table, ensuring no duplicates exist.",
64
"Processing features":
"Capabilities of a system or software to manipulate or transform data.",
65
"Project management":
"The process of planning, executing, and controlling a project to meet objectives within time and budget constraints.",
66
"Pseudocode":
"A simplified, human-readable version of programming logic used to design algorithms.",
67
"Quantitative Data":
"Measurable data that can be expressed in numerical terms, such as statistics or metrics.",
68
"Qualitative Data":
"Descriptive data that captures qualities or characteristics and is not easily measurable in numbers.",
69
"Relational Databases":
Databases structured to recognize relationships between tables, using primary and foreign keys.",
70
"Secondary Data":
"Data that has been collected by someone else, such as reports, articles, or government statistics.",
71
"Security Protocols":
"Rules and procedures for securing communication and data transfer over networks.",
72
"Security threats":
"Potential dangers to data security, such as malware, phishing, or hacking.",
73
"Software":
"Programs and applications that perform tasks on digital systems.",
74
"Software requirements specification (SRS)":
"A document detailing the functions, features, and constraints of a software product.",
75
"Software security controls – Software":
"Security measures within software, such as encryption or authentication, to protect data and systems.",
76
"Solution (digital)":
"A digital tool or system designed to solve a specific problem.",
77
"Solution Constraints":
"Limitations or restrictions in a solution, such as budget, time, or resources.",
78
"Solution Requirements":
"The features and functionalities a solution must include to meet user needs.",
79
"Solution Scope":
"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
"Table Normalization":
"A process in database design to organize tables to reduce redundancy and dependency.",
81
"Techniques for coding data":
"Methods for structuring and organizing data for analysis or storage.",
82
"Testing techniques":
"Methods used to ensure a solution or system works as expected, such as unit testing or system testing.",
83
"Threats - accidental":
"Unintentional actions or events that risk data, such as human error.
84
what is field type " text " used for?
Used for alphanumeric data, such as names, addresses, or international phone numbers.
85
what is field type " numeric " used for?
For numerical values where calculations are required (e.g., postcodes, tax file numbers).
86
what is field type " character " used for?
Single characters or special symbols, often used in coding or database fields.
87
what is field type " float " used for?
Decimal numbers used in calculations that require precision.
88
Existence Check
Ensures required fields are filled out to avoid incomplete data entries.
89
Type Check
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
Range Check
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
SUM():
Adds a range of cells together. Example: "=SUM(A1:A10)" calculates the total of values in cells A1 through A10.
92
AVERAGE():
Calculates the mean of a range of cells. Example: "=AVERAGE(B1:B10)" gives the average value in cells B1 through B10.
93
* IF():
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
Data Validation
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
Conditional Formatting:
Changes the appearance of cells based on their values. For example, highlighting cells in red where values are below a certain threshold.
96
Purpose id data visualisation:
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
Types of data visualisation:
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
Clarity- data visualisation
Visualisation should be easy to read and interpret, avoiding clutter or unnecessary elements.
99
Accuracy-data visualisation
Data should be represented faithfully, without distortion or misrepresentation. For example, starting a bar chart at zero to avoid exaggerating differences.
100
Aesthetics-data visualisation
Use of color, layout, and design should enhance the understanding of the data, not distract from it.
101
Guidelines for Creating Effective Charts:
* 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
Efficient Data Collection Techniques:
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
Data Alignment and Formatting Techniques
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
AND()- Logical Operators and their Usage
Returns TRUE if all conditions are met.
105
OR()- Logical Operators and their Usage
Returns TRUE if any one of the conditions is met.
106
NOT()- Logical Operators and their Usage
Reverses the result of a condition (i.e., TRUE becomes FALSE and vice versa).
107
Appearance Design Tools:
Include IPO (Input-Process-Output) charts, flowcharts, and wireframes to plan the look and feel of the application.
108
Functionality Design Tools:
Focus on the system’s operations and include tools like data flow diagrams (DFDs) and entity-relationship diagrams (ERDs).

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