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Why Enterprise Class Privacy Automation is now required

Risk & Compliance teams are faced with new challenges to enforce and demonstrate Privacy Compliance when using data for data science and/or when sharing data divisionally or with external data partners. Traditional data security approaches of encryption, hashing and tokenization applied ad hoc on a project by project basis is not enterprise-class, does not scale in a consistent manner across the business and of course exposes the enterprise to noncompliance and fines.

CryptoNumerics ‘Privacy Automation’ software is the next generation privacy management solution. It helps address the increasing demand for privacy control in a consistent and enterprise-class manner, harmonizing the key stakeholders to support data science and data collaboration use cases into a single software solution.
Recorded Sep 11 2019 60 mins
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Presented by
Ravi Pather (VP Sales CryptoNumerics), Craig Hawco (Senior Software Engineer CryptoNumerics)
Presentation preview: Why Enterprise Class Privacy Automation is now required

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  • Building Privacy Automation into Data Science Architectures Oct 2 2019 3:00 pm UTC 60 mins
    Ravi Pather (VP Sales CryptoNumerics), Craig Hawco (Senior Software Engineer CryptoNumerics)
    Enterprises face new challenges to approach data and privacy compliance in a consistent manner that is fully auditable, GDPR calls this, Data Protection by default and by design.

    In this webinar, you will learn about Privacy Automation, a new approach for Risk & Compliance teams to work together with Data Science teams to add business value. Additionally, Privacy Automation allows privacy governance and policy enforcement processes to be built into an organization's IT infrastructures.

    Privacy Automation can be built into existing Data Science technology stacks and pipelines and showing how governance and policy enforcement can be standardized.
  • Balancing Privacy Compliance and Data Science Sep 25 2019 3:00 pm UTC 60 mins
    Roberto Cervantes (Head of Marketing), Craig Hawco (Senior Software Engineer CryptoNumerics)
    In addressing various data privacy compliance, Risk and Compliance teams are enforcing policies for encrypting, hashing, or tokenizing customer data to the extent that it kills the analytical value required for Data Science. As a result, Data Science teams are finding it harder to perform their jobs.

    In this webinar, you will learn how CryptoNumerics ‘Privacy Automation’ software leverages Privacy Protection Actions that de-identify the data through anonymization and pseudonymization while still retains the analytical value of the in-direct identifiers required for data science.
  • Assessing the Risk Of Re-Identification for Privacy Compliance Sep 18 2019 3:00 pm UTC 30 mins
    Roberto Cervantes (Marketing @ CryptoNumerics), Hassan Bhatti (Business Development CryptoNumerics)
    Recent research has revealed the ease at which anonymized data, when combined with other available information, can reveal the identity of an individual. The outcome is non-compliance and therefore, risks of fines and reputational damage. GDPR encourages the use of 'state-of-the-art' technologies when available.

    In this webinar, you will learn:
    How to leverage state-of-the-art technologies to assess the risk of re-identification in your datasets automatically

    How to embed risk scoring into your GDPR and CCPA data compliance assessment processes based on an enterprise-class and consistent approach
  • Why Enterprise Class Privacy Automation is now required Recorded: Sep 11 2019 60 mins
    Ravi Pather (VP Sales CryptoNumerics), Craig Hawco (Senior Software Engineer CryptoNumerics)
    Risk & Compliance teams are faced with new challenges to enforce and demonstrate Privacy Compliance when using data for data science and/or when sharing data divisionally or with external data partners. Traditional data security approaches of encryption, hashing and tokenization applied ad hoc on a project by project basis is not enterprise-class, does not scale in a consistent manner across the business and of course exposes the enterprise to noncompliance and fines.

    CryptoNumerics ‘Privacy Automation’ software is the next generation privacy management solution. It helps address the increasing demand for privacy control in a consistent and enterprise-class manner, harmonizing the key stakeholders to support data science and data collaboration use cases into a single software solution.
  • Facilitating Multi-Site Research: Privacy, HIPAA and Data Residency Recorded: Jun 27 2019 40 mins
    Charles Boicey (Chief Innovation Officer Clearsense), Craig Hawco (Senior Software Engineer CryptoNumerics)
    Healthcare organizations, in most cases, may not have sufficient patient data to perform useful analytics e.g rare disease cohort analysis, gender-based analysis, and ethnicity-based analysis. This prevents them from doing evidence-based care as well as improving research outcomes. Consequently, hospital networks need to collaborate to overcome lack of data, however, due to HIPAA or data residency issues these collaborations are very cumbersome.


    In this webinar, you will learn from Charles Boicey, CIO ClearSense and a leading healthcare expert as well as Craig Hawco Senior Software Engineer, CryptoNumerics about a new way of doing collaborative analytics in a cost efficient, faster, and efficient way while satisfying regulatory requirements.
  • How to reduce privacy risk by creating privacy-protected datasets Recorded: Mar 28 2019 41 mins
    Jimmy Fan, Head of Engineering at CryptoNumerics. Roberto Cervantes, Head of Marketing at CryptoNumerics
    Data-driven organizations find themselves at a crossroad. On the one hand, they require data to make decisions and grow; on the other, privacy regulations limit the amount of data that can be accessed. Fortunately, there is a way to reconcile both.

    In this webinar you will learn:

    How to measure the privacy risk of a dataset
    What are the different privacy attributes in a dataset
    How to use CN-Protect to privacy-protect a dataset that can be used for analytics
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  • Title: Why Enterprise Class Privacy Automation is now required
  • Live at: Sep 11 2019 3:00 pm
  • Presented by: Ravi Pather (VP Sales CryptoNumerics), Craig Hawco (Senior Software Engineer CryptoNumerics)
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