How a Single Unified Data Platform Can Optimize Multiple Workloads

The expanded agility of a self-service, single data platform for all market customers provides profound advantages for the three major pharma teams in industrial, medical, and clinical activities.

FREMONT, CA: Nowadays, more businesses know that it is easier to own the data platform that pharma teams require instead of relying on outsiders. One firm predicted that next year, end consumers who have access to a curated data catalog would benefit twice as much from analytics as they do not.

In 2021, small and medium-sized life science firms will own their data systems to enable self-service connectivity and market mobility when they are most required. Underpinned by a shared data paradigm, this centralized data architecture is a cost-effective approach that offers an exact point of reality for all data—and uses cases—through business lines.

The expanded agility of a self-service, single data platform for all market customers provides profound advantages for the three major pharma teams in industrial, medical, and clinical activities. Collectively, it allows quicker reactions to evolving market conditions—like those created by COVID-19—for faster revisions and timely changes to business rules and KPIs to change launch cycles.

Instead of tracing together Individual components for computer engineering pipelines such as Extract, Transform, Load (ETL), and data quality software, companies can exploit a single investment in a centralized data framework that can be replicated by their various departments. Since a similar data model drives this approach, both agencies will use the same institutions for their respective purposes.

For a traditional patient-like entity, clinical surgery teams can use a model to monitor how many patients participated in the experiment, how many completed, what treatments they took, and how many were healed. Medical teams will review the same organization's analytics on all clinical trials' synopsis, providing them with information on the demographics of the treatment and the success rate to guide discussions with key opinion-makers. Commercial departments will analyze the same entity to reach patients and their physicians. As a substitute of monitoring these indicators with various tools, companies should use this centralized framework's shared data architecture with different predictive dashboards, which is far more cost-effective.