Connecticut Data Privacy Act

The CTDPA applies to individuals who conduct business in Connecticut or generate products or services aimed at inhabitants of the state, and who manage or process personal data of a specific number of residents.

The Trust Challenge

Obligations & Consequences

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

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The CTDPA applies to entities that conduct business in Connecticut that process the data of at least either.

  • (a) 100,000 Connecticut residents, with the exception of data collected only for the purpose of payment transactions, or


    (b) 25,000 Connecticut residents if the business derives more than 25% of its revenue from the sale of personal data."

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

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The CTDPA also establishes categories of exempt data.

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The CTDPA grants the consumer five basic data subject rights.

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Adoption of the “Data Minimization”, which implies that, organizations must collect & retain what is reasonably necessary and proportionate to the intended purpose.

The Trust Challenge

Challenges

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

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To facilitate its smooth implementation of CTDPA 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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Organizations lack the mechanism of validating the permanent deletion of the data.

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Manually managing data mapping and inventory, to adhere to CTDPA 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 CTDPA.

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

Win-Win Situation

Solutions

Ardent Privacy’s Solutions relating to the above mentioned challenges:

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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.

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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.

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“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.

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“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.

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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.

The Trust Challenge

Obligations & Consequences

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

Pointer

The CTDPA applies to entities that conduct business in Connecticut that process the data of at least either.

  • (a) 100,000 Connecticut residents, with the exception of data collected only for the purpose of payment transactions, or


    (b) 25,000 Connecticut residents if the business derives more than 25% of its revenue from the sale of personal data."

Pointer

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

Pointer

The CTDPA also establishes categories of exempt data.

Pointer

The CTDPA grants the consumer five basic data subject rights.

Pointer

Adoption of the “Data Minimization”, which implies that, organizations must collect & retain what is reasonably necessary and proportionate to the intended purpose.

The Trust Challenge

Challenges

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

Pointer

To facilitate its smooth implementation of CTDPA 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

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

Pointer

Manually managing data mapping and inventory, to adhere to CTDPA 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 CTDPA.

Pointer

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

Win-Win Situation

Solutions

Ardent Privacy’s Solutions relating to the above mentioned challenges:

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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