Data/AI Architecture for Pharma & MedTech

Big Data Stack:

Hadoop Ecosystem, Sqoop, Kafka, Rabbit MQ, Flume, Hive, Pig, Spark, Kubernetes, Object Storage, Tableau, NoSQL – Mongo dB, Cassandra

Services we provide for Data&AI architecture in Pharma/MedTech:

1) Build, optimize and maintain conceptual and logical database models in the enterprise data lake
2) Serve as a vital bridge from the business applications to technology architecture
3) Define logical and physical data model structures to store, integrate, govern, and maintain data in a secure and efficient manner while maintaining accuracy of the data in the enterprise data lake
4) Map to information entities that can define how information should flow and be consumed by various business functions and IT customers
5) Assist in strategy to bring the existing data models and their transformational logic from legacy warehouses to a modern big data platform to support analytics, reporting, machine learning and AI applications
6) Create source to target mappings between legacy warehouses and the future state in the data lake for various business domains
7) Identify impact on existing model/solution triggered by any new/changed requirements maintaining integrity of the models.
8) Hands on experience in building, optimizing the conceptual/logical database models and flow charts
9) Assist in defining corporate-wide data strategy and data governance and implementing data governance initiatives

Innovation Services related to Data architecture in Pharma/MedTech:

1) Lead data related workshops, design thinking sessions as part of customer interaction responsibility
2) Envision, lead and execute POV/POC/MVPs using extended teams
3) Demonstrate Deep domain expertise in data management, data warehousing and especially big data related next gen technologies
4) Have elevated conversation with the customers from business pain-point solving perspective