TEXT ANALYTICS DERIVING ACTIONABLE INSIGHTS FROM UNSTRUCTURED TEXT

whitePaper | September 28, 2022

Graph data science (GDS) is a scientific approach to gain knowledge from graphs, using the structures of connected data to power predictions, answer questions, and explain outcomes.

whitePaper | January 27, 2020

AWS maintains a standards-based risk management program to ensure that the HIPAA-eligible services specifically support the administrative, technical, and physical safeguards required under HIPAA. Using these services to store, process, and transmit PHI allows our customers and AWS to address the HIPAA requirements applicable to the AWS utility-based operating model.

whitePaper | August 20, 2021

While finding and creating insights can often feel like luck, there are proven methodologies you can use to ensure you’re seeing regular insight from your on-hand data. Access this short e-book to learn how you can start seeing regular, valuable insight success from you big data and analytics investments.

whitePaper | May 2, 2022

Download this white paper to get a step-by-step roadmap for adopting Dremio and migrating workloads while maintaining coexistence and interoperability with existing systems and technologies.

whitePaper | May 27, 2021

In many organizations, we need more collaboration between businesses, analytic teams, application developers and IT operations. These teams often work with data in silos and end up duplicating efforts, failing to integrate, or missing opportunities to deliver value from data. In addition to siloed efforts, data scientists are also faced with ever-increasing volumes and speeds of data. And the reality is they’re expected to answer questions just as fast as - or faster than - before. It’s important that we’re using the right data and the right techniques to ensure optimal outcomes. Download this guide to learn more about SAS and open source.

whitePaper | June 3, 2022

Analyzing data has been a unique business activity for at least 5,000 years, and possibly as long ago as 20,000 years. We have come a long way in how we count, summarize, analyze, predict, and prescribe upcoming courses of action in science, business, and all fields of human endeavor. In the past 75 years, the progress in how we analyze data has increased exponentially. We now regularly build analytical models and complete applications that analyze massive amounts of data.