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Tuesday, September 13 • 10:00am - 10:50am
Extend Security of Hadoop Environments

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Companies today have more vital information than ever, while data breaches are growing in pace and magnitude. It’s critical for companies to implement security solutions that control and audit everyone who accesses big data systems, not only because hackers are getting more sophisticated, but because the amount of data that’s at risk is increasing constantly. 

This session will focus on steps that organizations must take to secure and speed big data deployments. The global Hadoop market, powered by the rise in demand for big data analytics, is forecast to grow from $2 billion in 2013 to a staggering $50.2 billion by 2020, according to Allied Market Research.

However, security concerns related to Hadoop adoption threaten to slow the growth of big data technology. Hadoop clusters often contain sensitive personally identifiable information (PII) and other highly regulated data, so auditing and controlling user and administrator access to Hadoop and its underlying server infrastructure is critical to address both security and compliance requirements for regulations such as SOX, PCI and HIPAA. 

David will discuss how organizations can leverage existing Active Directory infrastructures to control access, manage privilege, address auditing requirements, and secure machine-to-machine communication with and across Hadoop clusters, nodes and services.

Speakers
avatar for David McNeely

David McNeely

VP of Product Strategy, Centrify Corporation
As VP of Product Strategy at Centrify, David works with customers to drive the roadmap for Centrify's award-winning identity and access management solutions. David has worked in the identity and access management industry for nearly 20 years and has held numerous product marketing and management positions at companies such as ActiveIdentity, AOL, iPlanet and Netscape. David is passionate about identity management and the future of cloud and... Read More →


Tuesday September 13, 2016 10:00am - 10:50am
DataWeek: Data Stage