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whitePaper | December 27, 2022

In this whitepaper we will define “data fabric,” look at different implementation strategies, and highlight the value of a logical approach. The paper will delve more deeply into the technical architecture of a logical data fabric and the key components to build a successful one, including the role played by artificial intelligence (AI) and data virtualization.

whitePaper | February 7, 2020

The problem is that growing volumes of data can lead to data paralysis, because no one knows quite where to begin or how to use it. Siloed information sources, no data management strategy, disconnected spreadsheets or analytical tools and poor data quality all work to compound the issues you’re facing.

whitePaper | September 12, 2022

Clinical Data Management (CDM) evolved over the last two decades from managing data entered on paper Case Report Forms (CRFs) to managing data transcribed into Electronic Data Capture (EDC) systems. The Society for Clinical Data Management (SCDM) strongly contributed to this first significant CDM evolution through its Good Clinical Data Management Practice 1 (GCDMP©) Chapters first published in 2000 and its certification program for Clinical Data Managers2 subsequently released in 2004.

whitePaper | December 1, 2022

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whitePaper | December 22, 2022

We live in a digital world in which data analytics and artificial intelligence significantly impact our daily lives. They influence what we wear, what we eat, where we travel, and how we spend our free time. In medicine the impact of data has much more drastic effects, as access to high-quality medical data is a matter of life or death for patients every day. In this particular area, the desire to save human life by discovering modern methods of therapy and diagnostics often contradicts another fundamental right of the patient - the right to privacy and the right to dispose of one’s data.

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.