By automating complex data management workflows, Metomic enables security teams to easily discover, classify and secure sensitive data across Google Workspaces
Metomic Unveils Powerful Data Discovery & Classification Solution to Manage & Secure Sensitive Data at Scale
Claire Wilson
claire.wilson@metomic.io
Metomic, a next generation data security and data loss prevention (DLP ) solution for protecting sensitive data in cloud-based work environments and SaaS ecosystems, today released its Data Classification solution, making it possible to discover, classify and secure sensitive data at scale across Google Workspaces. Metomic’s latest innovation is an AI-powered tool that automates complex data management Workflows, enabling IT and security teams to maintain control of their data while also ensuring data compliance across cloud-based storage and SaaS environments.
Without accurate data classification, businesses can’t prioritize risk, address vulnerabilities or implement effective security measures at scale downstream. With Metomic’s Data Classification solution, organizations can automate complex data workflows and implement “data rules” that ensure files are labeled appropriately within Google. It also makes it possible to create effective security controls that keep a business’ most sensitive data safe from becoming a data security risk (e.g. revoking public access to files marked ‘confidential’). Advanced classifying and tagging functionality is a key benefit for highly regulated industries—particularly healthcare and financial organizations—making it easy to adhere to strict regulations such as ISO27001, GDPR, CCPA, SOX, and HIPAA and reducing the risk of costly penalties associated with non-compliance.
Last year, McKinsey & Company surveyed global organizations with more than $100 million in annual revenue on their data management strategies. The survey findings revealed 82% of respondents reported spending one or more days per week resolving data quality issues and an astounding 66% were using manual review processes to “assess, monitor, and manage” the quality of their data. The findings underscore a critical need for innovative, automated solutions that enable companies to identify, classify, label—and secure—their data at scale.
“Understanding what sensitive data your employees are creating, where it’s stored, and how it’s being accessed and shared is critical, especially in today’s cloud-based work environments, like Google Drive,” said Rich Vibert, co-founder and CEO, Metomic. “Metomic’s data classification solution empowers IT and security teams to have complete control over their data management capabilities, automating key priorities and enabling a much more secure framework that minimizes data security risks, while vastly improving a company’s data management capabilities.”
By leveraging its proprietary data loss prevention technology, Metomic’s data classification solution allows security leaders to easily add, remove, and modify context-aware data labels across an entire data environment, ensuring data management classification protocols remain accurate and updated. Not only does Metomic make it possible to automate crucial data management tasks at scale, it enables security leaders to protect the company’s most sensitive data against emerging data security risks while maintaining compliance with evolving regulations.
To learn more about Metomic’s data classification solution, visit: https://www.metomic.io/solution/data-classification
About Metomic:
Metomic's data security software for SaaS, GenAI and cloud was born out of the frustration of its leaders trying to implement SaaS applications that make businesses more productive but are off limits because of high-risk security concerns. As a next generation security solution focused on cloud-based applications, Metomic gives security teams clear visibility into their organization’s SaaS network to manage sensitive data and detect security threats, allowing businesses to take full advantage of their SaaS application network. To learn more visit www.metomic.io.
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