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Globally, organizations are actively assessing the impact of GDPR on their business and data privacy and management operations. The deadline of May 2018 is looming, and any organization collecting PII of EU residents needs to work through the deployment of additional processes, policies and technologies to avoid the significant fines posed by the regulation.
By taking a holistic approach to GDPR compliance, organizations can better understand information security-related risk, how to prioritize investments to more effectively manage risk, establish accountability for risk management, and more quickly respond to identified gaps in the information security control framework.
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(2.18 MB)
pdf
(2.18 MB)
Globally, organizations are actively assessing the impact of the GDPR on their business and data privacy and management operations. The deadline of May 2018 is looming, and any organization doing business in the EU or processing PII from EU residents needs to working through the deployment of additional processes, policies and technologies to avoid the significant fines posed by the regulation.
Organizations must protect PII in a number of different ways, and must be able to demonstrate due diligence in keeping records of processing activities, including the categories of personal data processed, the purposes of processing, categories of recipients of PII, transfers to third countries, and the relevant technical and organizational security measures, as well as ensuring that only authorized users have access to the data.
Are you ready? General Data Protection Regulation (GDPR) enforcement begins May 2018. Don’t get derailed by last-minute planning efforts. Start making moves today to protect data against breaches and ensure data privacy—or face the threat of huge fines.
This guide is for CISOs who want to understand whether their companies will be impacted by the new regulation, what the effects might be, and steps their teams could take to prepare for GDPR data security requirements.
Hadoop is a unique architecture designed to enable organizations to gain new analytic insights and operational efficiencies through the use of multiple standard, low-cost, high-speed, parallel processing nodes operating on very large sets of data. The resulting flexibility, performance, and scalability are unprecedented. But data security was not the primary design goal.
Clear guidance on best practices for managing tempdb to provide the optimum balance between performance, reliability, and manageability.