UK Personal Data Protection Act | General Data Protection Act UK

The DPA empowers UK residents (consumers), provides a general description of data protection reforms since the UK left the EU and now has an approved adequacy decision.

The Trust Challenge

Obligations & Consequences

The following are few key obligations & consequences, flowing from the DPA, on any organization to whom these provisions apply:

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DPA requires that companies uphold the principle of “purpose limitation”.

  • Fairness/transparency
  • Purpose Limitation
  • Data Minimisation
  • Accuracy
  • Storage Limitation
  • Security
  • Accountability
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The regulation requires the organization to incorporate reasonable practices to fulfill the administrative, technical, and physical security.

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The DPA defines seven basic data subject rights: the right to be informed about how your data is used, to access personal data, to correct data, to have data deleted, to stop or restrict data processing, to data portability, and to object to how your data is processed.

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Users also have additional rights and protections under the DPA when their data is processed through automated decision-making or profiling algorithms.

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The DPA requires preparation of Incident Reporting & Breach Management Workflow.

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DPA requires the appointment of a Data Protection Officer for certain organizations, as well as maintaining a detailed record of processing activities.

The Trust Challenge

Challenges

Following challenges, emanating from the DPA requirements, are currently being encountered by various organizations:

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To facilitate its smooth implementation of DPA organizations ought to have their entire “Data footprint”.

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Organizations share the user data with various third parties, during the course of its business.

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Manually managing data mapping and inventory, to adhere to DPA requirements, such as verifying and fulfilling consumer requests (DSR’s) within the stipulated period, or else shall run the exposure of regulatory sanctions.

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Implementation of Data Minimization under DPA.

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Lack of provision or process to delete the data, despite the fact that the DPA mandates data deletion when the lawful basis for processing expires.

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Organizations lack the mechanism of validating the permanent deletion of the data.

Win-Win Situation

Solutions

Our AI-based, patented solution, TurtleShield PI (Privacy Intelligence) discovers all personal and sensitive data in structured and unstructured data systems across on-premises and multi-cloud environments. TurtleShield DI (Data Inventory) enables organizations to inventory & map their entire “Data footprint”, enabling them to protect what matters the most.

Often there are silos within entities or business and IT teams and it is challenging to get a full picture of data going outside organization and which is coming into organization, especially when data is shared with third parties, vendors, business partners and much more. Our TurtleShield PI (Privacy Intelligence) creates a data map based on your “data sharing”, to facilitate you to take action on it.

TurtleShield DM (Data Minimization) helps businesses minimize excess data and adhere to data minimization principle. This is data hygiene control and we are approaching it from a risk reduction and compliance perspective. We scan large data sets to scan for excess data using Machine Learning and find out excess data including personal data. This can eliminate operational inefficiencies and save cost by removing the unwanted data and legal cost of having it with respect to regulatory compliance.

With TurtleShield RTBF (Right to Be Forgotten) provides the businesses the capabilities to comply with mandatory deletion of personal data by providing the capabilities to delete the data on request along with the validation of the deletion.

Search capability in large datasets to fulfill data subject requests in totality and at rapid space. Assumption that data only exists in databases and nowhere else is often not reality as customer data exists in many sources. Using Machine learning and AI we crawl across data sources and predict where PII can exist.

The Trust Challenge

Obligations & Consequences

The following are few key obligations & consequences, flowing from the DPA, on any organization to whom these provisions apply:

Pointer

VCDPA requires that companies uphold the principle of “purpose limitation”.

  • Fairness/transparency
  • Purpose Limitation
  • Data Minimisation
  • Accuracy
  • Storage Limitation
  • Security
  • Accountability
Pointer

The regulation requires the organization to incorporate reasonable practices to fulfill the administrative, technical, and physical security.

Pointer

The DPA defines seven basic data subject rights: the right to be informed about how your data is used, to access personal data, to correct data, to have data deleted, to stop or restrict data processing, to data portability, and to object to how your data is processed.

Pointer

Users also have additional rights and protections under the DPA when their data is processed through automated decision-making or profiling algorithms.

Pointer

The DPA requires preparation of Incident Reporting & Breach Management Workflow.

Pointer

DPA requires the appointment of a Data Protection Officer for certain organizations, as well as maintaining a detailed record of processing activities.

The Trust Challenge

Challenges

Following challenges, emanating from the DPA requirements, are currently being encountered by various organizations:

Pointer

To facilitate its smooth implementation of DPA organizations ought to have their entire “Data footprint”.

Pointer

Organizations share the user data with various third parties, during the course of its business.

Pointer

Manually managing data mapping and inventory, to adhere to DPA requirements, such as verifying and fulfilling consumer requests (DSR’s) within the stipulated period, or else shall run the exposure of regulatory sanctions.

Pointer

Implementation of Data Minimization under DPA.

Pointer

Lack of provision or process to delete the data, despite the fact that the DPA mandates data deletion when the lawful basis for processing expires.

Pointer

Organizations lack the mechanism of validating the permanent deletion of the data.

Win-Win Situation

Solutions

Pointer

Data discovery, inventory and mapping: Our AI-based, patented solution, TurtleShield PI (Privacy Intelligence) discovers all personal and sensitive data in structured and unstructured data systems across on-premises and multi-cloud environments.
TurtleShield DI (Data Inventory) enables organizations to inventory & map their entire “Data footprint”, enabling them to protect what matters the most.

Pointer

Third party “Privacy Intelligence” (monitors third party sharing): Often there are silos within entities or business and IT teams and it is challenging to get a full picture of data going outside organization and which is coming into organization, especially when data is shared with third parties, vendors, business partners and much more. Our TurtleShield PI (Privacy Intelligence) creates a data map based on your “data sharing”, to facilitate you to take action on it.

Pointer

“Data Minimization”: TurtleShield DM (Data Minimization) helps businesses minimize excess data and adhere to data minimization principle. This is data hygiene control and we are approaching it from a risk reduction and compliance perspective. We scan large data sets to scan for excess data using Machine Learning and find out excess data including personal data. This can eliminate operational inefficiencies and save cost by removing the unwanted data and legal cost of having it with respect to regulatory compliance.

Pointer

“Right to be Forgotten (RTBF)” with Assured Deletion: With TurtleShield RTBF (Right to Be Forgotten) provides the businesses the capabilities to comply with mandatory deletion of personal data by providing the capabilities to delete the data on request along with the validation of the deletion.

Pointer

Enable Data subject rights with cost savings and compliance in totality: Search capability in large datasets to fulfill data subject requests in totality and at rapid space. Assumption that data only exists in databases and nowhere else is often not reality as customer data exists in many sources. Using Machine learning and AI we crawl across data sources and predict where PII can exist.

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