Indonesia's PDPL Compared To The GDPR

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The Indonesian Personal Data Protection Law (PDPL) is the latest data protection regulation that has been drafted closely following the principles set down by the GDPR. Aspects like data subject rights, lawful bases for data processing, clearly defined penalties, and data breach requirements provide an example of how similar the two are. However, there are equally critical differences between the two as well, including the powers of regulatory bodies, the scope of the laws, and the exact data covered by the law.

Understanding both the similarities and differences is pivotal for any organization hoping to comply with the PDPL and make any necessary adjustments in their internal operations as a result.

Technically, no. The GDPR aims to protect the data of all EU residents and citizens. Hence, whether an organization is based in the EU doesn't matter. If it handles EU residents' data, it is subject to the GDPR.

It might be. The GDPR enforces several obligations and requirements related to data processing on organizations. Not only do organizations need users' consent before processing their data, but they also need a valid processing basis, and need to ensure their third-party vendors are GDPR compliant as well, in addition to several other data protection requirements. Failure to comply with any of these means a hefty fine and tremendous reputational losses.

There's no active Indonesian body that enforces the PDPL. However, the PDPL does require the formation of such a body that would be answerable directly to the President. Its enforcement powers will be similar to that of the Commission in the GDPR.

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Discover shadow and cloud-native assets and accurately classify data

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Transform raw, unstructured files into data ready for model training and tuning

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Protect AI interactions with intelligent retrieval, response, and prompt firewalls

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Unstructured Data Governance
Manage and govern unstructured data to enable its safe use with generative AI

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Govern data for safe innovation

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Discover shadow and cloud-native assets and accurately classify data

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Unstructured Data Governance
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Data Access Governance
Monitor sensitive data access and prevent unauthorized use

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AI Governance
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