Eli Lilly & Company – Pharma
Automating Data
Processing with AWS
“To fully leverage our business intelligence, we needed a scalable, cloud-native data infrastructure providing real-time visibility, overcoming our current limitations.”
THE CHALLENGE
Lilly faced significant inefficiencies with manual data reporting for distribution, competitors, and sales. Data wrangling in Excel, coupled with SharePoint for Power BI, lacked scalability.
Accessing diverse data shapes and formats from various countries compounded the challenge, hindering reliable insights and strategic decision-making.
Accessing diverse data shapes and formats from various countries compounded the challenge, hindering reliable insights and strategic decision-making.
DISCIPLINES
Data Engineering, AWS Cloud Architecture, Data Automation
OUR APPROACH
Automated Data Pipelines,
Streamlined BI
Uptimal partnered with Lilly to integrate their existing AWS infrastructure, replacing manual file-based ingestion with API connections for a fully automated data cycle.
For data sources that do not yet offer API integration, including a variety of country-specific formats, we developed automated ingestion pipelines using AWS Lambda. Where possible, we also leveraged SharePoint’s API. This end-to-end data engineering approach automatically loads raw data into Redshift for storage. A subsequent Lambda function then transforms the data, preparing it for seamless use in Power BI. This streamlined process has substantially reduced dashboard complexity and enhanced performance.
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Diagnostic & Strategy
We conducted a deep dive into Lilly’s manual data reporting processes (distribution, competitors, sales), identifying inefficiencies and scalability limitations. -
Architecture & Integration
We designed an automated data ingestion architecture on AWS, utilizing API connections for primary sources and Lambda functions for SharePoint and other complex formats. -
Automation & Reliability
We implemented a full data engineering cycle: automated ingestion via Lambdas, storage in Redshift, and transformation for Power BI, ensuring reliable data and lightweight dashboards.
“We realized that automating data
ingestion and centralizing it
in AWS would not only solve
their manual process scalability
issues but also fundamentally
transform their analytical capabilities.”
Project Manager
RESULTS
Goals Accomplished!
Lilly now benefits from a modernized, automated data infrastructure integrated with AWS. This provides unprecedented data visibility, eliminating manual processes and significantly reducing transformation load on Power BI, enabling faster and more reliable strategic decision-making.
+80%
improvement on data ingestion speed
+100%
confidence in data quality
+45%
reduction in BI data prep time
improvement on data ingestion speed
confidence in data quality
reduction in BI data prep time
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