The Five Styles of Enterprise BI

whitePaper | November 24, 2022

Without a data-literate team, your company doesn’t have a chance of becoming data-driven. “Speaking data” is one of the biggest skills in the coming years as more technical skills (think SQL or R programming) become embedded in the tools themselves, demonstrating what we’ve always known — that tools will only take you so far. Your real resource is people.

whitePaper | December 21, 2022

The evolution of cloud-based technology is continuing to reshape the data management landscape. As data volumes increase, users in different industries are demanding flexible, scalable processes that enable them to leverage a wider variety of sources, uncover new insights and confidently make decisions that will drive their businesses forward.

whitePaper | September 12, 2022

This whitepaper examines clinical trial data contribution policies and the data protection methodologies applied to protect patient privacy. Information published by 29 biopharma sponsors was collected across three data-sharing platforms, collated by sponsor size. Results showed that large sponsor contribution policies can provide helpful benchmarks for medium and smaller sponsors.

whitePaper | November 15, 2019

Fault-tolerance is the ability for a system to remain in operation even if some of the components used to build the system fail. Even with very conservative assumptions, a busy e-commerce site may lose thousands of dollars for every minute it is unavailable. This is just one reason why businesses and organizations strive to develop software systems that can survive faults. Amazon Web Services (AWS) provides a platform that is ideally suited for building fault-tolerant software systems. The AWS platform enables you to build fault-tolerant systems that operate with a minimal amount of human interaction and up-front financial investment.

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 | December 29, 2022

Imagine that you are starting a family and you want to stay on top of your finances so you can manage your budget for your growing family. Because you have too many accounts for banking, loans, subscriptions, and bills to keep track of, you decide to sign up for a service that aggregates all your accounts in one place. When you register your account online, you follow the instructions carefully. You create a strong, unique password and set up multifactor authentication. You enter your bank account and loan information, home address, and other personal information. Your spouse also signs up, and you create a joint family account that combines your information.