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The client is a multinational pharmaceutical company based in India. 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 client wanted to improve and accelerate analytics-driven decisions and reduce the time for data analysis, data analytics, and data reporting on both structured and unstructured data. Furthermore, the client wanted to improve the deviation tracking of mitigation tasks and reduce the system stack cost by enabling an open-source, industrial-grade platform. The client also wanted to prepare ground and infra for AI/ML and advanced analytics.
We built enterprise data lake architecture and implemented analytics on the AWS platform. This solution included AWS data lake architecture for scalable warehouse and AWS data lake architecture for IoT and unstructured data.
The enterprise data lake architecture on the AWS platform enabled the client to process, analyze, and report both structured and unstructured data quickly with better analytics-driven decisions. This solution helped the client to reduce IT costs and improve business performance.
Aptus Data Labs used the following process to build enterprise data lake architecture for scalable warehouse and for IoT and unstructured data to resolve the business challenge. The solution was in three stages. Aptus Data Labs:
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: