VCE Vault

VCE Applied Computing: Data Analytics past exams 2023–2025

Every question from the last three VCE Applied Computing: Data Analytics exams, matched to the lesson that teaches it, with class averages from the examiners' reports and worked solutions. VCE Applied Computing: Data Analytics (Year 12) lessons.

2025 Exam

  • MC 1 (1 mark, class average 16%): Which visualisation type is interactive and can use static or live data. Lesson: Data Analytics and Visualisation
  • MC 2 (1 mark, class average 25%): A suitable technique for recording a project's progress. Lesson: Project Management Methodologies
  • MC 3 (1 mark, class average 86%): What a mood board is. Lesson: The Problem-Solving Methodology
  • MC 4 (1 mark, class average 83%): How to test whether a bar chart really represents the data. Lesson: Data Analytics and Visualisation
  • MC 5 (1 mark, class average 91%): First step when questionnaire data has spelling mistakes and gaps. Lesson: Data Analytics and Visualisation, Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 6 (1 mark, class average 74%): Best sign that a website source is authentic. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 7 (1 mark, class average 54%): How to collect secondary data on stars with high integrity. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 8 (1 mark, class average 68%): Which option is an emerging trend in cyber security. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery, Networks and Cybersecurity
  • MC 9 (1 mark, class average 87%): Which dashboard mock-up better meets an interactivity criterion. Lesson: User Experience Design, The Problem-Solving Methodology
  • MC 10 (1 mark, class average 75%): Which feature improves error tolerance when a filter hides all the data. Lesson: User Experience Design
  • MC 11 (1 mark, class average 64%): How to work out how long a project with parallel tasks will take. Lesson: Project Management Methodologies
  • MC 12 (1 mark, class average 90%): Formula to calculate monthly profit from income and expenses cells. Lesson: Data Analytics and Visualisation
  • MC 13 (1 mark, class average 62%): Which law covers how a federal agency collects, stores and uses personal data. Lesson: Ethics and Legal Issues in IT
  • MC 14 (1 mark, class average 45%): What characteristics of data types and structures mean when manipulating data. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity, Databases and SQL Fundamentals
  • MC 15 (1 mark, class average 70%): A technique that makes an infographic's information easy to understand. Lesson: Data Analytics and Visualisation
  • MC 16 (1 mark, class average 73%): Classify checking scores against a range and names against ID. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity, Data Analytics and Visualisation
  • MC 17 (1 mark, class average 51%): What APA stands for in APA referencing. Lesson: Ethics and Legal Issues in IT
  • MC 18 (1 mark, class average 60%): Which set of principles shapes a dashboard's appearance and functionality. Lesson: User Experience Design
  • MC 19 (1 mark, class average 94%): Classify a threat caused by a lightning strike and power failure. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • MC 20 (1 mark, class average 80%): First stage of a disaster recovery plan in an emergency such as a fire. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • B1 (2 marks, class average 15%): Identify and describe how to cite quotations in a report using APA. Lesson: Ethics and Legal Issues in IT
  • B2 (2 marks, class average 75%): Classify two statements as a goal or an objective. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • B3 (4 marks, class average 20%): Describe incremental and differential backups and their space and time needs. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • B4 (6 marks, class average 62%): Complete a Gantt chart around weekends and a public holiday. Lesson: Project Management Methodologies
  • B5a (1 mark, class average 32%): Name the SQL operation that lists only customers who have matching orders. Lesson: Databases and SQL Fundamentals
  • B5b (1 mark, class average 27%): Explain why that SQL operation suits this task. Lesson: Databases and SQL Fundamentals
  • B5c (4 marks, class average 53%): Show the result of joining the customer and order tables. Lesson: Databases and SQL Fundamentals
  • C1 (2 marks, class average 35%): Name a feature of a strong research question and explain it. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C2 (2 marks, class average 10%): List two non-functional requirements for the careers infographics. Lesson: The Problem-Solving Methodology
  • C3a (3 marks, class average 47%): Suggest and justify the most efficient way to collect primary data from professionals. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C3b (4 marks, class average 40%): Explain two ways to make sure the primary data is collected ethically. Lesson: Ethics and Legal Issues in IT, Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C4a (2 marks, class average 40%): Give the data type and field size for two student fields. Lesson: Databases and SQL Fundamentals
  • C4b (3 marks, class average 33%): Explain how primary and foreign keys link the two tables, with an example. Lesson: Databases and SQL Fundamentals
  • C5a (3 marks, class average 53%): Complete an IPO chart for the 2020 enrolment total. Lesson: The Problem-Solving Methodology, Data Analytics and Visualisation
  • C5b (1 mark, class average 59%): Name the spreadsheet function for the IPO chart's process. Lesson: Data Analytics and Visualisation
  • C6a (3 marks, class average 80%): Sketch a three-section mock-up for the first careers infographic. Lesson: The Problem-Solving Methodology, Data Analytics and Visualisation
  • C6b (3 marks, class average 23%): Annotate the mock-up to explain space, alignment and balance. Lesson: User Experience Design, Data Analytics and Visualisation
  • C7a (1 mark, class average 11%): Explain what validation is and when it happens. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity, Data Analytics and Visualisation
  • C7b (3 marks, class average 67%): Identify the validation check needed for three problem cells. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity, Data Analytics and Visualisation
  • C8a (2 marks, class average 60%): Using an example, explain why the enrolment table needs cleansing. Lesson: Data Analytics and Visualisation, Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C8b (2 marks, class average 25%): Describe a process to cleanse the table properly. Lesson: Data Analytics and Visualisation
  • C8c (3 marks, class average 43%): Describe how to quickly calculate the average enrolments for every year. Lesson: Data Analytics and Visualisation
  • C9 (4 marks, class average 63%): Complete a testing table for an enrolments chart. Lesson: Data Analytics and Visualisation
  • C10 (4 marks, class average 18%): Outline an evaluation strategy for an eye-catching, interesting criterion. Lesson: The Problem-Solving Methodology
  • C11a (1 mark, class average 33%): Identify the type of incident. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C11b (1 mark, class average 12%): Which Act covers this kind of incident. Lesson: Ethics and Legal Issues in IT
  • C11c (1 mark, class average 29%): Describe the actions the legislation requires after the incident. Lesson: Ethics and Legal Issues in IT, Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C12 (4 marks, class average 33%): Define data accuracy and give three consequences of diminished data integrity. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity, Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C13a (1 mark, class average 10%): Explain why the disaster recovery plan should be tested. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C13b (3 marks, class average 20%): Outline a strategy to confirm that all files were restored successfully. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C14a (3 marks, class average 43%): Fill in a hash table for a seven-character password. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery, Networks and Cybersecurity
  • C14b (1 mark, class average 46%): Deduce the hashed version of the password. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery, Networks and Cybersecurity

2024 Exam

  • MC 1 (1 mark, class average 90%): What a database query is for. Lesson: Databases and SQL Fundamentals
  • MC 2 (1 mark, class average 29%): Best design tool for showing how a spreadsheet worksheet will look. Lesson: The Problem-Solving Methodology, Data Analytics and Visualisation
  • MC 3 (1 mark, class average 31%): Which problem-solving stage includes querying large data repositories. Lesson: The Problem-Solving Methodology, Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 4 (1 mark): Which feature is not a convention of an infographic. Lesson: Data Analytics and Visualisation
  • MC 5 (1 mark, class average 90%): Best name for a database table of sales data. Lesson: Databases and SQL Fundamentals
  • MC 6 (1 mark): The main purpose of an infographic. Lesson: Data Analytics and Visualisation
  • MC 7 (1 mark, class average 89%): Best technique for improving an infographic's effectiveness. Lesson: Data Analytics and Visualisation, User Experience Design
  • MC 8 (1 mark, class average 96%): Classify an interactive, zoomable map of house prices. Lesson: Data Analytics and Visualisation
  • MC 9 (1 mark, class average 92%): Best way to keep more than 100 sensor data files organised. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 10 (1 mark, class average 30%): What to check when assessing how effective a project plan is. Lesson: Project Management Methodologies
  • MC 11 (1 mark, class average 88%): Best way to choose between two design ideas for an infographic. Lesson: The Problem-Solving Methodology
  • MC 12 (1 mark, class average 68%): A recommended practice for verifying data. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity, Data Analytics and Visualisation
  • MC 13 (1 mark, class average 87%): Main advantage of a wired network in a clothing store. Lesson: Networks and Cybersecurity
  • MC 14 (1 mark): Which law a small NSW health business breaks by giving away client contact details. Lesson: Ethics and Legal Issues in IT
  • MC 15 (1 mark, class average 83%): Safest backup option after an events-based threat. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • MC 16 (1 mark): Most important integrity characteristics for a teacher's class data. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 17 (1 mark, class average 70%): An example of diminished data integrity when charting landmark heights. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 18 (1 mark, class average 80%): Data types for a letter grade and an attendance count. Lesson: Databases and SQL Fundamentals, Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 19 (1 mark, class average 76%): Which data type is best for calculating averages and finding patterns. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 20 (1 mark, class average 60%): Choose the best research question about pet ownership and teenagers' happiness. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • B1a (2 marks, class average 65%): Describe biometrics as a physical control and why the organisation should use it. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • B1b (2 marks, class average 65%): Describe shredding confidential documents and why the organisation should do it. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • B2a (2 marks, class average 45%): Explain why the rewards points field needs a range check. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity, Data Analytics and Visualisation
  • B2b (3 marks, class average 37%): Write a query design that finds customers eligible for the upgrade. Lesson: Databases and SQL Fundamentals
  • B3a (1 mark, class average 20%): One way to confirm the photo backup worked. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • B3b (2 marks, class average 35%): Explain two concerns with the friend's suggested backup method. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • B4 (4 marks, class average 20%): Justify which audience characteristic matters most for a bank presenting to lenders. Lesson: User Experience Design, Data Analytics and Visualisation
  • B5a (2 marks, class average 15%): Give one criterion to evaluate the company's current data security and explain it. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • B5b (2 marks, class average 50%): Recommend a strategy to stop bots breaking in to a password-protected portal. Lesson: Networks and Cybersecurity, Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C1a (3 marks, class average 70%): Circle three errors in the project's Gantt chart. Lesson: Project Management Methodologies
  • C1b (3 marks, class average 53%): Describe how to fix each Gantt chart error identified. Lesson: Project Management Methodologies
  • C2a (4 marks, class average 55%): State and describe two methods for collecting the shops' purchasing data. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C2b (4 marks, class average 43%): Describe two advantages of one of those collection methods. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C3a (2 marks, class average 35%): Describe one concern about supplying too much data. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C3b (3 marks, class average 53%): Decide whether to use sales data from North American ski shops and explain why. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C4 (6 marks, class average 20%): Give a functional requirement, a constraint and a scope item for the visualisations. Lesson: The Problem-Solving Methodology
  • C5 (4 marks, class average 8%): Write one efficiency and one effectiveness criterion for the design ideas. Lesson: The Problem-Solving Methodology
  • C6 (4 marks, class average 35%): Explain one functionality and one appearance design principle in the user controls. Lesson: User Experience Design
  • C7 (3 marks, class average 57%): List three conventions that would make the snow depth graph readable. Lesson: Data Analytics and Visualisation
  • C8 (2 marks, class average 35%): Identify two software functions needed to build the dynamic visualisations. Lesson: Data Analytics and Visualisation
  • C9a (2 marks, class average 65%): Pick one entry in the snow depth data and explain its lack of integrity. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C9b (4 marks, class average 43%): Describe how to cleanse and validate the snow depth data efficiently. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity, Data Analytics and Visualisation
  • C10 (2 marks, class average 15%): Describe a test that checks the dynamic visualisations show the right data. Lesson: Data Analytics and Visualisation
  • C11 (3 marks, class average 47%): Recommend how to manage files still needed but not used by the visualisations. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C12 (2 marks, class average 35%): Explain why customer and supplier data matters to the business. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C13 (4 marks, class average 57%): Recommend two security controls that would have stopped the files being accessed. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C14a (1 mark, class average 37%): Identify the law that applies to a consultant holding Victorian government data. Lesson: Ethics and Legal Issues in IT
  • C14b (2 marks, class average 30%): Explain why that law is relevant to the consultant. Lesson: Ethics and Legal Issues in IT
  • C14c (2 marks, class average 50%): Outline one issue with how the consultant is storing the data. Lesson: Ethics and Legal Issues in IT, Data and Information Security — Threats, Security Controls and Disaster Recovery

2023 Exam

  • MC 1 (1 mark, class average 50%): Best data type for a mobile phone number field in a customer database. Lesson: Databases and SQL Fundamentals
  • MC 2 (1 mark, class average 91%): Pick the clearest field name for a cat's birthday. Lesson: Databases and SQL Fundamentals
  • MC 3 (1 mark, class average 90%): Which characteristics describe a spreadsheet's functionality rather than its appearance. Lesson: User Experience Design
  • MC 4 (1 mark, class average 76%): Write the criteria for cars made after 2020 from either of two countries. Lesson: Databases and SQL Fundamentals
  • MC 5 (1 mark, class average 69%): Which list is made up only of digital system components. Lesson: Networks and Cybersecurity
  • MC 6 (1 mark, class average 26%): Classify a constraint based on the level of expertise of the users. Lesson: The Problem-Solving Methodology
  • MC 7 (1 mark, class average 42%): Choose the best research question about video games, sleep and results. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 8 (1 mark, class average 82%): General characteristics of qualitative data. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 9 (1 mark, class average 70%): Which integrity characteristic suffers when two students' data is missing. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 10 (1 mark, class average 38%): Pick a criterion that tests both efficiency and effectiveness of a visualisation. Lesson: The Problem-Solving Methodology, Data Analytics and Visualisation
  • MC 11 (1 mark, class average 91%): How a team can stop losing track of the right versions of its files. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • MC 12 (1 mark, class average 30%): Which interactive feature makes a flu-vaccination comparison quickest to use. Lesson: Data Analytics and Visualisation
  • MC 13 (1 mark, class average 28%): Which text feature helps an infographic communicate survey findings to its audience. Lesson: Data Analytics and Visualisation, User Experience Design
  • MC 14 (1 mark, class average 32%): Best chart for showing the relationship between three variables. Lesson: Data Analytics and Visualisation
  • MC 15 (1 mark, class average 53%): Best way to protect the files kept on an office network. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • MC 16 (1 mark, class average 56%): Most efficient way to get the whole student body's feedback on a visualisation. Lesson: The Problem-Solving Methodology, Acquiring Data — Collection Methods, Data Types and Data Integrity
  • MC 17 (1 mark, class average 63%): What is usually included in a disaster recovery plan. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • MC 18 (1 mark, class average 92%): Classify data loss caused by a lightning strike. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • MC 19 (1 mark, class average 90%): A likely result of an organisation having weak information security. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • MC 20 (1 mark, class average 90%): Identify the physical security control in a list. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • B1 (4 marks, class average 15%): Design related database tables for a furniture delivery app. Lesson: Databases and SQL Fundamentals
  • B2a (1 mark, class average 48%): Outline a technique for generating design ideas for an infographic. Lesson: The Problem-Solving Methodology
  • B2b (2 marks, class average 55%): Describe one appearance design principle that suits an elderly audience. Lesson: User Experience Design
  • B2c (3 marks, class average 63%): Justify which of two infographic designs better communicates to elderly readers. Lesson: The Problem-Solving Methodology, User Experience Design
  • B3a (2 marks, class average 35%): Explain how navigation differs from error tolerance in a dynamic visualisation. Lesson: User Experience Design
  • B3b (1 mark, class average 22%): Give a technique for testing navigation in a visualisation. Lesson: User Experience Design, Data Analytics and Visualisation
  • B3c (1 mark, class average 14%): Give a technique for testing error tolerance in a visualisation. Lesson: User Experience Design, Data Analytics and Visualisation
  • B4a (2 marks, class average 50%): Maximum days of data lost when restoring from this backup routine. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • B4b (4 marks, class average 65%): Suggest and justify two changes to improve a backup strategy. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C1a (2 marks, class average 25%): Identify two items that belong in the project's scope. Lesson: The Problem-Solving Methodology
  • C1b (2 marks, class average 30%): Identify two constraints on developing the visualisation. Lesson: The Problem-Solving Methodology
  • C2a (4 marks, class average 28%): Complete a Gantt chart from a task table, avoiding weekends. Lesson: Project Management Methodologies
  • C2b (1 mark, class average 43%): List the tasks that are not on the critical path. Lesson: Project Management Methodologies
  • C2c (2 marks, class average 30%): Explain why those tasks are not on the critical path. Lesson: Project Management Methodologies
  • C3 (7 marks, class average 54%): Design a labelled online survey input form for the grain facility consultation. Lesson: The Problem-Solving Methodology, Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C4a (1 mark, class average 21%): Give one reason the free-text survey comments must be coded. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C4b (2 marks, class average 25%): Explain how to code the comments so they can be visualised. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C5 (4 marks, class average 48%): Identify and explain two network components the farmers need to send sensor data. Lesson: Networks and Cybersecurity
  • C6a (2 marks, class average 55%): Explain how a software security control protects data while it is being sent. Lesson: Networks and Cybersecurity, Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C6b (2 marks, class average 50%): One advantage and one disadvantage of storing data on network attached storage. Lesson: Data and Information Security — Threats, Security Controls and Disaster Recovery
  • C7 (2 marks, class average 55%): Justify whether an anonymous blog post should be used as a data source. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C8 (1 mark, class average 67%): Why the research team should reference the sources it uses. Lesson: Ethics and Legal Issues in IT
  • C9a (2 marks, class average 25%): Name two components that make up a GIS data set. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity
  • C9b (2 marks, class average 10%): Explain how GIS data helps make the visualisation effective. Lesson: Data Analytics and Visualisation
  • C10 (3 marks, class average 40%): Match a design tool to each part of the visualisation project. Lesson: The Problem-Solving Methodology
  • C11 (2 marks, class average 30%): Explain a technique for recording project progress on the Gantt chart. Lesson: Project Management Methodologies
  • C12a (4 marks, class average 45%): Describe two techniques to validate the weather data in the spreadsheet. Lesson: Acquiring Data — Collection Methods, Data Types and Data Integrity, Data Analytics and Visualisation
  • C12b (3 marks, class average 13%): Describe one technique to test that the spreadsheet works. Lesson: Data Analytics and Visualisation
  • C13a (2 marks, class average 20%): One format and one convention for comparing five years of rainfall across three regions. Lesson: Data Analytics and Visualisation
  • C13b (2 marks, class average 15%): Explain why the chosen chart type best informs the audience. Lesson: Data Analytics and Visualisation
  • C13c (2 marks, class average 30%): Outline a feature that would make the rainfall chart dynamic. Lesson: Data Analytics and Visualisation
  • C14 (4 marks, class average 13%): Propose two measurable factors for assessing how effective the project plan was. Lesson: Project Management Methodologies
  • C15 (2 marks, class average 55%): Should the CEO worry about passing farmers' contact details to a fertiliser company?. Lesson: Ethics and Legal Issues in IT