Life sciences and Bio Pharma companies, small to large scale, in recent years have realized the importance of insights for effective drug launches in the market. It is no more the muscle power of the organization's sales and marketing team that guarantees the success of a new launch but is the ability of the organization to gather and leverage actionable Patient Insights, Physician Insights and Payer Insights effectively that makes the difference.
Companies procure data sets like CRM data, HCP/HCO Master data, Specialty Distribution data, among others for such use cases. Typically, these data sets are stored in data lakes or data warehouses. Building an effective, secure, and scalable data store is challenge which many enterprises are trying to solve.
Further drilling down, it becomes evident that there are 4 main aspects on which an effective data lake or data warehouse must deliver on:
- Data Integration & Preparation
- Data Democratization
- Data Lineage
- Data Ops & Governance
Based on analyst reports on an average it takes 6 to 9 months to build a data lake. Companies which are looking to launch will need the data infrastructure in a few weeks and require an alternative approach to achieve this.
In this webinar, we will talk about how a framework driven solution brings together all the aspects mentioned above in a single platform while specifically providing acceleration for life sciences and pharma companies.
- Karthik Mohan is working as a Product Architect at D Cube Analytics with 14 years of experience building Cloud/On Premise based Data Analytics Platforms and Products.
- Subidya Bharati is working as an Associate Product Architect at D Cube Analytics with 12 years of experience specializing in BI Solutions and Data Management within Cloud and On-Premises Platforms.