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VCE Data Analytics U4O2 · Modules 1–25

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A free printable VCE Data Analytics U4O2 definitions worksheet with 10 key terms, built from the key terms of Why data security matters and types of threats and Data integrity and its consequences (Modules 1–25) — Goals and objectives of medium and large organisations, Safeguarding business operations, Mitigating financial loss and reputational damage, Accidental threats to data, Deliberate threats to data, Events-based threats to data and more. Print it or save it as a PDF — the answer key starts on its own page. No login needed.

VCE Data Analytics U4O2 Definitions Worksheet: Why data security matters and types of threats and Data integrity and its consequences (Modules 1–25)

Name:
Date:
Class:

Key terms

Write what each term means, in your own words.

1
organisational goals and objectives
2
business continuity
3
Mitigation
4
accidental threat
5
deliberate threat
6
events-based threat
7
Authenticity
8
Correctness
9
reasonableness
10
timeliness

Answer Key

VCE Data Analytics U4O2 · Modules 1–25 · Student wording will vary for definitions
1organisational goals and objectives — Goals are broad aims like growth, profit and customer trust. Objectives are measurable steps toward them. Both depend on secure, reliable data.
2business continuity — Keeping systems and data working so daily business can carry on. Security limits downtime so services keep running when a threat or failure occurs.
3Mitigation — Using strong security to cut the money lost (fines, recovery costs, lost customers, falling share price) and the damage to brand and public trust after a data incident.
4accidental threat — Harm to data caused by a mistake with no intent to cause damage, such as emailing the wrong person, deleting files by accident, misconfiguring sharing or losing a device.
5deliberate threat — An intentional action by an attacker or malicious insider to steal, damage, alter or block access to data, usually for profit or revenge.
6events-based threat — An event outside anyone's control, such as fire, flood, storm or power failure, that damages data or systems or blocks access to them.
7Authenticity — Data is authentic when it genuinely comes from the source it claims and has not been forged or spoofed. Verifying its origin shows it can be trusted.
8Correctness — Data is correct when it is in the right form and follows set rules, such as the right data type, format, valid values and calculation. It is not the same as accuracy.
9reasonableness — Data is reasonable when its value is sensible and believable in its context, so impossible values or odd outliers (like an age of 250) are flagged by reasonableness checks.
10timeliness — Data is timely when it is up to date and available when needed. Out-of-date records or delayed updates can lead to poor time-critical decisions.

Modules this definitions worksheet covers

Every module has its own free printable worksheet with an answer key, and students can practise the same terms interactively on Cloodit.

Part of: VCE Data Analytics - U4O2 - Cyber Security: Data Security, ACARA Digital Technologies Years 7–8 — Networks and Cyber Threats, ACARA Digital Technologies Years 9–10 — Acquiring and Validating Data, ACARA Digital Technologies Years 9–10 — Cyber Security Threats and Vulnerabilities, QCE Digital Solutions Unit 2 — Data-Driven Problems and Solution Requirements, QCE Digital Solutions Unit 4 — Complex Digital Data Exchange Problems and Solution Requirements

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