Visualizing data across platforms with a unified, customized data mart
Context
The client is a leading US-based physicians' practice service provider.
They provide medical outsourcing and hold a large share of the market. They partner with a multitude of affiliated companies, providing worldwide services for outsourcing physicians to related segments.
Business problem
The client had a unified but aging legacy data mart. They wanted to pull data for various reports and dashboards across platforms without writing extensive and complex code logic since this logic had already been incorporated into the client's tables. The client's analytics team needed to use their tables fast - but this required IT intervention to push them to production.
Expected goals
Key goals required included:
Execute the project without compromising requisite data quality or making the process too complex - all while populating the new, optimized data mart.
Solution
Fast deployment of solution with optimized pipelines
The solution delivered to the client included:
Created new pipelines to pull data from source tables by applying transformation logic and loading data into final tables
Using cutting-edge tech to trigger processes on a daily basis
The solution was deployed using:
ELT Process: Python
Cloud hosting: AWS (DMS, Secret Manager, S3, Airflow)
Database: Snowflake
Outcomes of the Engagement
Better visualization of data improved decision-making abilities
Enhanced control over visualizing data
The solution helped the client to populated required tables with accurate data for better visualization and analysis utilizing Snowflake.
Improved data-driven decision-making capabilities
Improvement in deriving key insights from the data enhanced decision-making capabilities.
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Key project outcome metrics:
More data marts populated