Treatment pathways analytics on fever drug portfolio
Multinational pharmaceutical company with a diverse drug portfolio.
The client wanted to apply big data analytics on their fever drug portfolio subjects to understand the clinical treatment pathways using real-world evidences and electronic health records. The client did not have enough information to enable analysis across multiple systems to generate a systematic analytical output.
SG Analytics' data scientists provided a comprehensive big data solution, where data from multiple systems in different formats was cleansed, transformed and aggregated to enable batch processing and advanced analytics.
Our team mapped, aggregated and standardized data from various sources for fever drug portfolio.
The team set up an Extract-Transform-Load (ETL) mechanism for data acquisition and analyzing the data quality.
We loaded the data into a staging area in Hadoop technology. After the staging layer, the team ensured that data was converted into HDFS module in parquet format.
We applied advanced analytical models and visualization on the data marts for faster prediction and efficient insight generation.
The team monitored the model continuously and re-calibrated the same for better results.
Provided and maintained an enterprise-wide big data warehouse for clinical analytics.
Designed analytical models and data visualization tools to establish effective pathways prediction for faster and improved insight generation.