The CCPA empowers California residents (consumers), by enabling them with more power & control over how their data is collected, used, shared and sold.

The Trust Challenge

Challenges

Following challenges, emanating from the CCPA/CPRA requirements, are currently being encountered by various organizations:

  • To facilitate it’s smooth transition from CCPA, to CPRA, organizations ought to have their entire “Data footprint”
  • Organizations share the user data with various third parties, during the course of its business.
  • Manually managing data mapping and inventory, to adhere to CCPA requirements, such as verifying and fulfilling consumer requests (DSR’s) within the stipulated period, or else shall run the exposure of regulatory sanctions.
  • Implementation of Data Minimization under CPRA.
  • Lack of provision or process to delete the data, despite the fact that the CPRA mandates data deletion when the lawful basis for processing expires.
  • Organizations lack the mechanism of validating the permanent deletion of the data.
Win-Win Situation

Solutions

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

  • “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.
  • 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.
  • “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.
  • “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.
  • 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

Challenges

Following challenges, emanating from the CCPA/CPRA requirements, are currently being encountered by various organizations:

  • To facilitate it’s smooth transition from CCPA, to CPRA, organizations ought to have their entire “Data footprint”
  • Organizations share the user data with various third parties, during the course of its business.
  • Manually managing data mapping and inventory, to adhere to CCPA requirements, such as verifying and fulfilling consumer requests (DSR’s) within the stipulated period, or else shall run the exposure of regulatory sanctions.
  • Implementation of Data Minimization under CPRA.
  • Lack of provision or process to delete the data, despite the fact that the CPRA mandates data deletion when the lawful basis for processing expires.
  • Organizations lack the mechanism of validating the permanent deletion of the data.
Win-Win Situation

Solutions

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

  • “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.
  • 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.
  • “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.
  • “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.
  • 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.

Featured News, Blogs & Events

Be the first to catch our latest updates,
happenings and more.

Follow us