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The Data Scientist's Guide to Preserving Privacy

As personal data becomes abundant, the risk of sensitive data being leaked or misappropriated has become much greater. This risk is greatly exacerbated by the ability to augment publicly available data. This occurs, in part, because aggregation erodes privacy—the combination of disparate and seemingly trivial bits of personal information can be used to infer sensitive personal attributes. Consequently, organizations seeking to maintain trust with their customers must have robust frameworks in place to preserve privacy within their curated data and when those sources are joined with external data.

In this webinar, we present practical approaches to maintain privacy and highlight the vulnerabilities of each approach within the analytics workflow. We discuss, in detail, three common techniques for data privatization: masking, k-anonymization, and differential privacy. For each technique, we ground the discussion in a case study that highlights the trade-offs between data utility, privacy preservation, and robustness against linkage attacks.

You will walk away with:

- A framework for identifying privacy risks in their own analyses
- Multiple approaches that can be used to preserve privacy
- An understanding of how to make decisions that balance utility and privacy
Recorded Dec 19 2019 60 mins
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Presented by
Alfred Rossi, Research Scientist, and Stephen Bailey, Data Scientist
Presentation preview: The Data Scientist's Guide to Preserving Privacy

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  • The Data Scientist's Guide to Preserving Privacy Recorded: Dec 19 2019 60 mins
    Alfred Rossi, Research Scientist, and Stephen Bailey, Data Scientist
    As personal data becomes abundant, the risk of sensitive data being leaked or misappropriated has become much greater. This risk is greatly exacerbated by the ability to augment publicly available data. This occurs, in part, because aggregation erodes privacy—the combination of disparate and seemingly trivial bits of personal information can be used to infer sensitive personal attributes. Consequently, organizations seeking to maintain trust with their customers must have robust frameworks in place to preserve privacy within their curated data and when those sources are joined with external data.

    In this webinar, we present practical approaches to maintain privacy and highlight the vulnerabilities of each approach within the analytics workflow. We discuss, in detail, three common techniques for data privatization: masking, k-anonymization, and differential privacy. For each technique, we ground the discussion in a case study that highlights the trade-offs between data utility, privacy preservation, and robustness against linkage attacks.

    You will walk away with:

    - A framework for identifying privacy risks in their own analyses
    - Multiple approaches that can be used to preserve privacy
    - An understanding of how to make decisions that balance utility and privacy
  • The Governance Challenge: Managing your Data to Maximize Insights Recorded: Nov 13 2019 47 mins
    Cory Minton, Sidd Tewar, Stephen Bailey & Pankaj Dugar
    Ensuring your data is secure and well-governed is an essential component of any successful data-driven strategy in today's competitive marketplace. Maintaining a firm handle on your approach to data security, governance and compliance will help streamline your analytics processes and keep your data flowing to obtain quality insights that drive business value. But compliance can be challenging to navigate and the logistics behind securing your data without compromising accessibility aren't always clear.

    Listen in as this panel of industry experts dive into the topic of managing your business data to maximize insights. You'll discover:

    - Data governance best practices
    - The data security issues that matter when it comes to organizing your data for analytics
    - How to navigate common compliance hurdles without sacrificing control

    Cory Minton, Founder & Editor in Chief, BigDataBeard (Moderator)
    Sidd Tewari, Cloud Architect, Immuta
    Stephen Bailey, Data Scientist, Immuta
    Pankaj Dugar, VP, Business Development, ISVs and Tech Partners
  • Enhancing Privacy in Data Science and Analytics Recorded: Nov 13 2019 23 mins
    Stephen Bailey & Cory Minton
    In the last two decades, the ability to collect personal information on individuals has opened up a new frontier, fueling innovation and enabling companies and organizations to deliver better, more personalized services at scale. But innovation carries risks, and this new frontier is rife with them. Organizations must proactively develop controls and processes to guard personal data in order to have sustained success in a data-driven world.

    In this interview with Stephen Bailey, Data Scientist at Immuta, we will explore methods for transforming data in a manner that protects the privacy of individuals while preserving utility and discuss the challenges and opportunities of privacy-aware analytics.

    Speakers:
    Stephen Bailey, Data Scientist, Immuta
    Cory Minton, Founder & Editor in Chief, BigDataBeard
  • Enabling Data Consumers with Secure Cloud-Based Data Lakes Recorded: Sep 25 2019 45 mins
    Sidd Tewari, Cloud Architect, at Immuta
    Despite the staggering investments being made in analytics, business intelligence, and database management systems, many organizations are still struggling to extract value from their data and analytics initiatives.

    Why? According to recent research from Gartner, the reasons vary:
    - Difficulty deploying into existing business processes and applications
    - Inability to demonstrate return on investment
    - Inability to adequately secure or govern the data or analytical inputs and outputs from their initiatives

    In this session, Sidd Tewari, Cloud Architect at Immuta, will demystify cloud-based data lakes and share how cloud-based data lakes can enable data consumers across your organization to securely and easily access and use valuable data.

    About the speaker:
    With 15 years of technology experience, Sidd has been immersed in cloud technologies since 2010. In early 2014, Sidd joined CloudHealth Technologies (acquired by VMware), where over the course of 5 years he acquired first-hand knowledge of market trends and cloud adoption use-cases ranging from new businesses with a cloud-first approach to traditional enterprises beginning their cloud journey. At Immuta, as a cloud architect, he has been focused on cloud-based enterprise data governance, interacting heavily with AWS, Google, Databricks, and Snowflake.
Automated Data Governance
Immuta gives you granular, dynamic control of who accesses your data and why — without copying data or writing a single line of code. The result is instant data self-service with powerful security and oversight.

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  • Title: The Data Scientist's Guide to Preserving Privacy
  • Live at: Dec 19 2019 6:00 pm
  • Presented by: Alfred Rossi, Research Scientist, and Stephen Bailey, Data Scientist
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