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Driving Cloud Migration & Analytics at Scale | Industry Insights | Technology Partners

Written by Insights Contributor | Sep 6, 2024 10:01:12 PM

Analytics at scale to push innovation

Our healthcare research client’s executive leadership team envisioned a future that enabled best-in-class translational research by empowering researchers to do their best work. This future state would drive research innovation and enable AI and team science at an entirely new scale, all while improving governance, security, and compliance.

The challenge

More than 30 different highly-regulated healthcare business units leveraged the existing data environment. Major cloud providers had yet to consistently produce strong cloud infrastructure and platform engineering, let alone integrate with best-in-class translational research and HIPAA-compliant cloud environments.

The plan

We took an iterative approach and developed a cloud data fabric built on Databricks in Azure. This fabric allowed the aforementioned departments to migrate their data assets to the cloud and expand upon their current capabilities. Users are now empowered to ingest data from a wide variety of data sources (RDBMS, APIs, file systems, Synapse, Big Query, etc.) without the need to write code for the majority of scenarios.

The results

The results speak for themselves:

  • New Reporting Standards
    We created an organizational source of truth for trusted reporting across the enterprise.
  • Flexible Data Analytics
    We ensured that 30+ departments enjoyed flexible, independent data environments (clusters), enabling more options for analytics tools.
  • Controlled Data Sharing
    We facilitated data sharing in a governed manner, both internally and externally, at the push of a button.
  • Improved User Development
    We fostered user development through native Databricks tools, such as Notebooks.
  • Direct Notebook Integration
    We gave our client the ability to embed Notebooks directly into the data pipeline, allowing for custom transformations.
  • User Query Optimization
    We made certain that user queries could be saved, shared, and improved upon across the enterprise.