Privitar, BigID Partner to Reduce Risk and Gain Insight for Privacy-Protected Data Pipelines
LONDON and BOSTON, JUNE 3, 2020 – Privitar and BigID partnered to provide organizations with an integrated, automated approach to tackling some of the biggest challenges associated with deriving valuable insights from sensitive data. The integration of Privitar’s privacy engineering platform and policies with BigID’s data discovery and classification ensures that analytics teams can make use of well-defined, high resolution, de-identified datasets for their programs, and remove manual steps for privacy-aware data pipeline provisioning.
To support the launch of the partnership, Privitar and BigID will co-host a special webinar with Amazon Web Services entitled “Automating Safe Data Analytics for Financial Services” on June 11, 2020.
“Timely data access and minimizing privacy risk are critical success factors for today’s data leaders,” said Jason McFall, CTO of Privitar. “The partnership between Privitar and Big ID makes both of these possible, enabling enterprises to leverage their data safely and at great speed.“
Today, data engineering and data science teams depend on data derived from multiple sources to drive new insights. Combining data from multiple sources amplifies the risks that individual data subjects are inappropriately profiled or re-identified. Also, privacy compliance mandates such as the EU GDPR and the California Consumer Privacy Act limit the use of data to the assigned purpose of processing. Organizations must be able to reliably classify and provision personal data for use in a way that respects and adheres to current privacy requirements, including consistent understanding of who the data belongs to.
The integration of BigID’s machine learning-driven discovery, classification, and labeling for sensitive and personal data, combined with Privitar’s comprehensive de-identification, policy management and data provisioning enables data-driven enterprises to both streamline and de-risk their data pipelines. API-level integration of sensitive data discovery and policy-driven de-identification allows for automated metadata exchange, and enables fast, efficient and standardized data protection and provisioning at scale. Organizations can maximize the value of their sensitive data by realizing seamless data discovery, programmatic tagging of categories, automated data provisioning, and consistent privacy preservation.
With Privitar and BigID, organizations can leverage their most sensitive data whether it is in the cloud, on-prem or hybrid, and fuel their digital transformation across analytics, data lake, machine learning and artificial intelligence initiatives.
Through the integrated solution, customers can:
- Accelerate time from data ingestion to data usage by building privacy into their data pipelines
- Identify and classify sensitive data to automatically apply privacy protections
- Quickly find and prepare data for analyses and models without coding or scripting
- Eliminate slow, error-prone manual data scrubbing processes and automate Safe Data provisioning at scale
- Systematically adhere to privacy policies and procedures, with the ability to audit actions
- Consistently apply privacy protections across all data sources and environments
“The integration of Privitar and Big ID provides a powerful and scalable approach to sensitive data discovery and analytics across the entire enterprise,” said Nimrod Vax, CPO of BigID. “Our customers can draw on the combined discovery and performance at scale of BigID and Privitar technologies to make data available while preserving privacy for a wide range of use cases in a secure, seamless, and orchestrated process.
To learn more about the Privitar and BigID partnership, visit: https://bigid.com/partner/privitar/
To learn more about Privitar and Big ID’s webinar, visit: https://www.privitar.com/resources/automating-safe-data-analytics-for-financial-services/
Organizations worldwide rely on Privitar to protect their customers’ sensitive personal data and to deliver comprehensive data privacy that frees them to extract maximum value from the data they collect, manage and use. Founded in 2014, Privitar is headquartered in London and has offices in New York, Boston, Munich, Paris and Singapore. For more information, please visit www.privitar.com.
Based in New York, BigID uses advanced machine learning and identity intelligence to help enterprises better protect their sensitive, customer, and employee data at petabyte scale. Using BigID, enterprises can better safeguard and assure the privacy of their most sensitive data, reducing breach risk and enabling compliance with emerging data protection regulations like the EU’s General Data Protection Regulation and California Consumer Privacy Act. BigID has raised $146 million in funding since its founding in 2016 and has been recognized for its privacy innovation as the 2018 RSA Conference Innovation Sandbox winner, a CB Insights 2018 Cyber Defender, Network Products Guide 2018 IT World Awards “Hot Company of the Year” winner, a 2019 InformationWeek Vendor to Watch, a 2019 Business Insider enterprise vendor “to bet your career on,” and a 2019 World Economic Forum Technology Pioneer. Learn more at http://bigid.com or visit us at http://bigid.com/demo to schedule a demo.
Source: BigID and Privitar