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The Rare Disease Cures Accelerator–Data and Analytics Platform (RDCA-DAP®) is launching a new webinar series with the goal of sharing with the community examples of the use of rare disease person-level data in drug development and regulatory decision making. The series will feature 1-hour webinars highlighting analyses that have been done in individual disease areas, how they informed drug development, and how similar approaches could be applied to common drug development issues encountered in rare diseases. After each presentation time will be allowed for discussion with a panel of Quantitative and Regulatory experts around why the solutions presented were informative, lessons learned and how similar approaches could be applied to related problems.

Modern data applications and analytics rely on a wide variety of data both inside and outside the company; organizations depend on enriched data sets for better insights. This need, in part, has driven many companies to move to cloud data warehouses and cloud data lakes. However, it’s no longer simply about migrating to the cloud. It’s about modernizing using a combination of industry-leading services in the cloud and cloud-native data management services to deliver better business decisions, faster.

As data and analytics environments become increasingly complex, organizations can no longer afford to perform many operations manually. According to TDWI research, automation (in general) is one of the top three priorities for analytics. We see automation occurring throughout the data and analytics life cycle. Automation increasingly leverages embedded AI/ML algorithms (i.e., infused in the software) to help perform tasks such as profiling and cleansing data, identifying sensitive data, data mapping, surfacing insights, or building machine learning models.