Data Protection Impact Assessment

Learn to identify when DPIAs are required, assess privacy risks using likelihood and impact scoring, document appropriate mitigation measures, and understand when DPO consultation is necessary. Master the structured approach to privacy risk management that GDPR requires before any high-risk processing can begin.

What You'll Learn

  • Recognize common cybersecurity threats
  • Respond appropriately to security incidents
  • Protect sensitive information
  • Follow security best practices
  • Report suspicious activities

Training Steps

  1. Introduction

    You are Alice, Privacy Manager at HealthFirst Analytics. Your company is preparing to launch an AI-powered health analytics platform that will process patient health records at scale. Under GDPR Article 35, a Data Protection Impact Assessment (DPIA) is mandatory before processing that is 'likely to result in a high risk' to individuals' rights and freedoms. This includes automated decision-making, large-scale processing of special category data, and systematic monitoring.

  2. DPIA Request

    You receive an email from the Chief Technology Officer informing you that the new AI Health Analytics platform is entering final development. Before it can launch, you must complete a DPIA. The platform triggers DPIA requirements for three reasons: it processes health data (special category under Article 9), uses automated decision-making, and operates at large scale.

  3. Accessing the Risk Assessment Tool

    You need to log into the internal portal to access the Risk Assessment tool. This tool guides you through the structured DPIA process required by GDPR.

  4. Opening the Risk Assessment Tool

    The Risk Assessment tool provides a structured framework for assessing privacy risks - calculating risk scores based on likelihood and impact, then documenting mitigation measures. The tool displays risk categories on the left and a risk matrix on the right. You will assess each risk category by setting likelihood and impact scores.

  5. Understanding the Risk Matrix

    Before assessing individual risks, you need to understand how the risk matrix works. Risk is calculated as: Likelihood x Impact = Risk Score Both likelihood and impact are scored 1-5: Likelihood: How likely is this risk to occur? (1 = Rare, 5 = Almost Certain) Impact: How severe would the consequences be? (1 = Negligible, 5 = Catastrophic) Risk levels: 1-4 Low (green), 5-9 Medium (amber), 10-16 High (orange), 17-25 Critical (red).

  6. Assessing Data Breach Risk

    The first risk category is Data Breach Risk. With 2 million patient health records, a data breach would be catastrophic. Consider: The platform processes highly sensitive health data. Healthcare is a prime target for cyberattacks. A breach could expose diagnoses, treatments, and genetic information. Assess this risk with Likelihood: 3 (Possible - healthcare is frequently targeted) and Impact: 5 (Catastrophic - health data breach affecting millions).

  7. Setting Data Breach Scores

    Set the risk scores for Data Breach. Why these values? Likelihood: 3 (Possible) - Healthcare is one of the most targeted sectors for cyberattacks. While you have security controls, the threat landscape means breaches are realistically possible, not just theoretical. Impact: 5 (Catastrophic) - A breach of 2 million patient health records would cause severe harm: identity theft, discrimination, psychological distress. Health data is among the most sensitive - you cannot change your medical history like you can change a password. Risk Score: 3 x 5 = 15 (High) - This requires documented mitigation measures.

  8. Assessing Consent Management Risk

    The second risk is Consent Management. The platform relies on patient consent to process health data for analytics purposes. Consider: Patients must give explicit consent for health data processing. Consent must be freely given, specific, informed, and unambiguous. Withdrawal must be as easy as giving consent. Assess this risk with Likelihood: 2 (Unlikely with proper systems) and Impact: 4 (Major - processing without valid consent violates GDPR fundamentals).

  9. Setting Consent Management Scores

    Set the risk scores for Consent Management. Why these values? Likelihood: 2 (Unlikely) - With a properly designed consent system, invalid consent is unlikely. The platform uses clear consent forms, granular options, and documented withdrawal processes. Impact: 4 (Major) - Processing without valid consent is a fundamental GDPR violation. It could invalidate your entire legal basis and result in enforcement action, but it is not as immediately harmful to individuals as a data breach. Risk Score: 2 x 4 = 8 (Medium) - Manageable with standard controls.

  10. Assessing Data Retention Risk

    The third risk is Data Retention. Health analytics requires historical data, but GDPR mandates storage limitation. Consider: How long is data kept? Is there automatic deletion? Are retention periods documented and enforced? Old data increases breach exposure. Assess this risk with Likelihood: 2 (Unlikely with defined policies) and Impact: 3 (Moderate - retaining data too long violates storage limitation but is less severe than a breach).

Knowledge Check Questions

This training includes a 6-question quiz to test your understanding of Security Awareness threats and defenses.

  • When is a Data Protection Impact Assessment (DPIA) required under GDPR Article 35?
  • How is risk calculated in a DPIA risk assessment?
  • Which processing activities typically trigger a mandatory DPIA? (Select all that apply)
  • What mitigation measures help reduce data breach risk? (Select all that apply)
  • When must the Data Protection Officer (DPO) be consulted during a DPIA?

Category: Security Awareness Security Training

Duration: Approximately 43 minutes

Format: Interactive 3D Simulation

Provider: RansomLeak Security Awareness Training