The Evolution of Clinical Data Management to Clinical Data Science

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 | June 3, 2021

Data growth continues at an exponential rate even as cloud architectures make data management more complex and advanced applications necessitate more data movement. So what can be done to enable clean data capture and movement across an enterprise? Read this white paper to learn the requirements for data orchestration at scale and discover how you can build a holistic data architecture that enables successful DataOps.

whitePaper | March 12, 2020

In recent months, my company (Baron Consulting) has been proactively involved in setting up Data Collection Systems for a range of Private and Public Organisations we are servicing. Some of the data collection challenges have already been discussed in our recent Raw Data Collection 2020: Principles and Challenges White Paper. While the RDC (Raw Data Collection) paper analysed the current state of the everchanging Data Collection requirements, it did not have the scope to address technicalities of the RDC processes along with the specific Data Collection tools and methods. The purpose of this paper is to fill the void by looking into implementation of the automated data collection processes.

whitePaper | August 9, 2022

This report shows you how a data catalog can help you easily find and then use the data you need.

whitePaper | September 23, 2022

The COVID-19 pandemic times will go down in the annals of history as the ones which saw organizations face significant disruption in the way they executed their frontend business and backend operations. The pandemic waves have made organizations do the unthinkable – allowing their workforce to either operate exclusively from their homes, or at a minimum, distribute their working hours between home and office.

whitePaper | April 7, 2021

Assembling the perfect data stack is impossible. But for most data teams, the path to leveraging rapidly evolving tech and best-in-class tools is even more difficult when it’s impeded by the pitfalls of monolithic legacy applications.