Modernizing Clinical Data Management to Be Scalable, Flexible, and Intelligent

whitePaper | August 18, 2022

The 2022 data connectivity survey pivots somewhat from prior years’ studies. Data connectivity and data integration are well established in the traditional on-premise computing environment. But we’ve seen that as organizations increasingly expand their domains to one or more cloud service providers, it is important to better understand the challenges and opportunities for connectivity presented by modernization initiatives.

whitePaper | March 3, 2023

In today’s world, data is king and has become a major source of competitive differentiation for businesses across all industries. The COVID-19 pandemic has further accelerated the use and importance of data as the world’s governments and businesses adapted.

whitePaper | May 18, 2021

Next-gen data operations require next-gen data technologies and strategies and Azure is an ideal platform for this modernization to take place. Download this white paper to better understand the strategies, philosophies, and technologies your organization needs to expand analytics abilities, reduce technical debt, embrace AI, and more.

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.

whitePaper | September 6, 2022

Data is the heartbeat of the modern enterprise. Technology has progressed to the point that data-driven decision making is the norm and data literacy is often prized above all other skills.

whitePaper | October 17, 2022

Today, massive amounts of data are collected, processed, and stored for a range of analytical purposes around the world. Every customer, device, transaction, email, and image leaves a data trail. At present, this data is growing too big, changing too fast, and becoming hyper distributed. The traditional ways of doing integration and analytics are no longer viable or scalable. It is not feasible to create millions of data pipelines and to continue moving large amounts of raw data to a data lake or a centralized data warehouse.