DCPLA Exam Dumps : DSCI Certified Privacy Lead Assessor

The complexity of implementing data security for personal information is often influenced by operational and architectural factors such as:

A: Collecting data through various channels like web forms, mobile apps, customer support, etc., which introduces complexity in tracking and securing each channel.

B: Flexible and dynamic business processes that evolve rapidly can complicate access management due to frequent changes in user roles, workflows, and data access needs.

While regulatory requirements (C) do impact privacy governance, they do not directly contribute to the complexity of implementing technical security measures.

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The “Privacy Organization and Relationship (POR)” practice area of the DSCI Privacy Framework focuses on:

Establishing a dedicated privacy function

Allocating adequate resources (human and technical)

Defining roles and responsibilities for privacy across organizational layers

It includes the evaluation of whether the organization has the capability (skills and capacity) to manage its privacy obligations effectively — precisely the scope described in this assessment scenario.

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As per the official DSCI Privacy Framework (DPF©), the framework is built upon a set of nine core Privacy Principles that are foundational to establishing and assessing privacy initiatives in an organization. These principles are as follows:

Notice– Individuals must be informed about the collection and use of their personal data.

ChoiceandConsent– The data subject’s choice must be respected through consent mechanisms.

Collection Limitation– Personal data must be collected only for identified purposes.

Use Limitation– Data should be used only for the purposes specified at the time of collection.

Data Quality– Ensuring data is accurate, complete, and kept up-to-date.

AccessandCorrection– Data subjects must have access to their data and the ability to correct it.

Security– Adequate protection of personal data against unauthorized access and breaches.

Openness– Organizations must be transparent about their privacy practices.

Accountability– The entity collecting and processing data is responsible for complying with the principles.

These match exactly with the components listed in option A: I (Use Limitation), II (Accountability), III (Data Quality), IV (Notice), V (Preventing Harm—not explicitly named in DPF, hence not part of the standard nine), VI (ChoiceandConsent), VII (Access and Correction), VIII (Data Minimization), IX (Openness).

Hence, the correct nine principles according to DPF© are exactly as listed in option A.

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