BUSA8030 Chap.13 Data Law, Security and Emerging Technologies
Data Law, Security and Emerging Technologies
Week 10 moves from ethics to law. It asks what law is, how it differs from ethics and what legal uncertainty businesses face: the legal environment for collecting and using data, consistency across countries in storing, transmitting and integrating data and using AI, and the impact of technologies the law has not yet caught up with.
The lecture surveys national rules, pointing to Australia's Privacy Act and its penalties and India's new digital personal data protection law, before focusing on the European Union.
The GDPR applies to organisations outside the EU if they operate there, with fines that can reach tens of millions of euros.
Its seven principles are lawfulness, fairness and transparency; purpose limitation; data minimisation; accuracy; storage limitation; integrity and confidentiality; and accountability, which requires the controller to demonstrate compliance with the rest. The principles double as a practical design checklist for any analytics proposal.
Security is treated as a maturity issue: the lecture links it to corporate governance of data security, consumer control features, data breaches and their public fallout, and system hacking, and says meeting these challenges needs both modern technology and well-trained people.
Week 11 turns to emerging technologies and case practice.
New technologies provide new data sources, allow rapid improvement in analysis, learn more about human behaviour and enable autonomous, decentralised decision-making. IoT, 5G and 6G, blockchain, cloud computing, AI and machine learning each change decision-making in a specific way.
Cases such as Shell's digital transformation and AI in Australian agriculture illustrate the themes, and guidance for group presentations asks teams to state the problem, its quantitative and qualitative aspects, the solution, its benefit and the evidence behind it.
What this chapter covers
- 01
Law, ethics and business uncertainty
- 02
Security as a maturity issue
- 03
National data laws
- 04
The seven GDPR principles
- 05
Emerging technologies and decision-making
- 06
Case practice and pitching
Worked example · free
AskSia practice weighting: a GDPR check on an analytics proposal
- 1Transparency fails: customers are not told about the use.
- 1Purpose limitation fails: future, unspecified models are not a stated purpose.
- 1Data minimisation fails: full history exceeds what a defined purpose needs.
- 1Storage limitation fails: indefinite retention has no purpose-based limit.
- 1Changes: state the purpose, collect only needed signals, set deletion periods and document compliance.
Key terms
- General Data Protection Regulation
- The EU's 2018 data protection law, which applies to organisations targeting people in the EU.
- Purpose limitation
- The principle that data may be processed only for the purposes stated at collection.
- Data minimisation
- The principle of collecting and processing only as much data as the purpose requires.
- Storage limitation
- The principle that identifying data is kept only as long as the purpose requires.
- Internet of Things
- Networked devices that generate and pre-process data for real-time decisions.
- Blockchain
- A technology supporting transparent, trusted exchange of information among parties or devices.
Data Law, Security and Emerging Technologies FAQ
How does the law differ from ethics in Week 10?
The lecture treats ethics as what organisations ought to do and law as what governments require and enforce. Governments are turning more ethical expectations into law because technology moves faster than voluntary restraint.
What are the seven GDPR principles?
Lawfulness, fairness and transparency; purpose limitation; data minimisation; accuracy; storage limitation; integrity and confidentiality; and accountability, under which the data controller must be able to demonstrate compliance.
Why is data security described as a maturity issue?
Week 10 links analytics maturity to how firms govern data security, give consumers control, handle breaches and defend against hacking, all of which require trained people as well as technology.
How do emerging technologies change decision-making?
Week 11 explains that IoT generates real-time data, 5G and 6G move it quickly, cloud computing stores and processes it, AI and machine learning find patterns, and blockchain supports trusted exchange.
What should a group presentation include?
State the problem, define its quantitative and qualitative aspects for the country and organisation, state the solution and its benefit, and support the claim with references, pitching rather than summarising the report.
Assessment move
Use the seven GDPR principles as a checklist for the data section of your group plan, even if your organisation operates outside Europe.
One sentence per principle shows responsible design and connects your proposal to course content.
When an organisation in your report adopts an emerging technology, pair the benefit with the governance question it raises: where data is stored, whether inferences are fair, who is accountable.
That pairing is the critical move the unit rewards.
Before the presentation, rehearse the four-part pitch: problem, quantitative and qualitative evidence, solution and benefit, and the references behind it. Practise until each member can deliver their part within the time limit.
Working through Data Law, Security and Emerging Technologies in BUSA8030? Sia is AskSia’s AI Management tutor — ask any BUSA8030 Data Law, Security and Emerging Technologies question and get a clear, step-by-step explanation grounded in how BUSA8030 is taught and assessed. Read this chapter free, then take your hardest questions to Sia.
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