ZL Tech Introduces New Solution to Transform Out-of-Sight Corporate Knowledge to Business Insight

ZL Tech, the leader in unstructured information management, announced advancements to its SaaS platform that leapfrog today’s “sandbox” analytics paradigm by expanding the sandbox to the entire “beach.” The application enables organizations to extract insights buried in people data such as emails and documents, which embodies the human side of the organization. In doing so, companies can now answer essential questions about people, projects, and teams, such as:

• Who has the most impact?
• Who knows what?
• What does my workforce care about? And how do they feel?

Answers to these questions cannot be found in any database, but instead lie in the information shared every day by humans. This data has tremendous value because it represents all human dynamics, knowledge, participation and intent. However, it can only be fully realized by maximizing the breadth, depth and speed of data analytics across the enterprise.

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ZL Tech’s people analytics technology represents a different approach to taming unstructured data, overcoming previous obstacles with four completely new differentiators:

• Virtual or “In-Place” Data Management: The massive volume of unstructured data in the enterprise makes it compelling to manage “virtually” or “in-place” so as to avoid the cost and risk of making another data copy. ZL Tech enables the flexibility of managing the bulk of the unstructured data virtually (no copy), while for high-value data which typically comprises 2% to 5%, archiving a copy for governance requirements.
• From Sandbox to Beach: Most approaches to analytics start with selectively feeding data into a “sandbox.” The underlying assumption behind this step is that it would be impossible to scour the entire “beach.” However, most valuable information lies out of sight, outside the narrow sandbox. Accordingly, ZL Tech can search on demand through the entire beach of employee-created content, such as Microsoft 365, Teams, and file servers, to provide far more complete and relevant data feeds for analytics repositories.
• 1,000X Faster Time-to-Data: The traditional approach to analytics involves accessing the original data and exporting it, adding tremendous latency and scaling issues for large data sets. ZL Tech enables organizations to immediately search, cull, and perform iterations to arrive at a quick data set for export.
• Embedded Governance: To date, analytics has operated independently of governance obligations. However, new governance requirements such as privacy point toward a merging of governance and analytics processes. For example, management of unstructured data is required to adhere to privacy policies on the use of personal data. ZL’s unified approach to data management ensures that both governance and analytics requirements are satisfied simultaneously.

“Analytics today is just a sandbox. The insights are only as good as the data you throw into the sandbox,” said Kon Leong, CEO and co-founder of ZL Tech. “But enterprises that seek to be liberated from the sandbox can now expand data-wrangling to the beach, while also ensuring that governance obligations are met.”

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