Enterprise-Wide Democratization of AI/ML
In the next few years, Enterprise-wide adoption of AI and Cloud would dramatically increase and the ability to build/utilize AI solutions will move from highly specialized data scientists to other Data Citizens as well. Pharma organizations should adopt a wholistic approach in democratizing their AI and Cloud assets to ensure ease of adoption, seamless governance, and strict compliance in order to be successful. Some of the barriers to this are:
- Overhead effort in installing, setting up, maintaining, and connecting with enterprise data ecosystems with strong security and compliance.
- Fragmented AI/ML Ecosystem, inconsistent technology usage, lack of trust, duplication of effort and difficulty in collaboration.
- Leadership’s lack of ability to understand, estimate and monitor the Analytics costs across people and technology.
In this Webinar, we will be discussing about how a wholistic approach can be adopted by enabling a unified governance ecosystem which strikes a balance between governance and ease of use enabling organizations to adopt AI/ML freely.
- Sammed Kumar is a technical product manager at D Cube Analytics, has 15+ years of Industry experience in Data and Analytics, Data governance and syndication. Sammed has managed various initiatives in the areas of building Pharma MDM platforms, Data Warehouse, and advanced personalization.
- Samuel Jaideep is an Associate Product Architect at D Cube Analytics, has 7+ years of Industry experience in Web Technologies and Cloud Engineering. Jaideep has been involved in architecting and development of various Web Applications for multiple clients in the course of time.
- Meda Ajay Krishna is an Associate Product Architect at D Cube Analytics. He brings close to 7+ years of experience in Cloud – DevOps and product planning. He has experience in designing network and security for various applications. He has experience in designing Data Engineering and Pharma MDM platforms.