A P T U S D A T A L A B S

Loading

Implemented a distributed data lake architecture and advanced analytics on the AWS cloud platform to reduce IT costs and improve productivity

Revolutionizing Pharma Analytics with AWS Data Lake

The client is a multinational pharmaceutical company based in India. Moreover, the client deals in manufacturing and selling active pharmaceutical ingredients and pharmaceutical formulations in India and the US. Considered as one of the most reputed brands in India, the client has expanded with joint ventures and acquisitions in the last two decades.

The new data architecture based on AWS Cloud benefited the client in multiple ways and helped to resolve the business challenge. The benefits in all the three phases were:

  1. Advanced analytical capabilities-driven on both structured and unstructured data with Enterprise search enabled for any data
  2. Machine Learning used to drive improvements and productivity
  1. Demonstrated connectivity to various databases from Presto
  2. Backed up email and uploaded data to the cloud
  3. Uploaded IoT data to the cloud
  1. Established connectivity from R/Python to Cloud Database/S3 using Libraries
  2. Enabled Presto/AWS Athena for data search or ad-hoc queries
  3. Migrated Tableau dashboard to Superset or AWS Quicksights or D3.J3

Related Case Studies

Achieving low-latency API-based queries with Mongo DB

Performance analysis - MapR DB vs. Mongo DB - Tool Selection Process

Revolutionizing Pharma Analytics with AWS Data Lake

Enterprise Data Lake and Analytics implementation for a large Pharmaceutical Company in India on AWS platform

Boosting Performance with Apache Spark Migration

Data Migration & Performance Improvement of large data processing

If you’re looking to take your business to the next level with data science, we invite you to contact us today to schedule a consultation. Our team will work with you to assess your current data landscape and develop a customized solution that will help you gain valuable insights and drive growth.