Data Platform Modernization for Life Sciences
Migrate from legacy infrastructure to cloud-native, AI-ready data platforms – with GxP-compliant governance, semantic layers, and automated BI migration.
90%
Processing time improvement and $150K licensing savings via full-stack modernization
$750K
Annual savings and 40% error reduction via unified manufacturing analytics
100+
Reports migrated from Tableau to Power BI with automated conversion
The Problem CDOs and Data Leaders Face
Every life sciences company wants to be AI-ready. Few have the infrastructure to support it. The typical pharma data landscape is a patchwork of Oracle data warehouses, Informatica ETL pipelines, departmental SQL Server databases, and vendor-hosted analytics tools – none designed for modern AI workloads.
This legacy infrastructure creates three problems. First, it cannot support the data volumes and processing speeds modern analytics requires. Second, it lacks the governance and semantic layer needed for trusted AI. Third, it is expensive to maintain. Platform modernization is not optional – it is the prerequisite for every other analytics and AI ambition.
What We Do
We modernize life sciences data platforms with cloud‑native, AI‑ready architectures, automated BI modernization, and GxP‑compliant governance to accelerate trusted insights at scale.
Cloud Data Platform Migration
We migrate from Oracle, Teradata, SQL Server, and other legacy platforms to Snowflake, Databricks, and Microsoft Fabric. Our Flash Migrate accelerator handles assessment, conversion, validation, and cutover – compressing timelines by 20–40%.
Data Integration Modernization
We replace legacy ETL pipelines (Informatica, SSIS, DataStage) with modern integration tools (Fivetran, dbt) that are code-based, version-controlled, and easier to maintain.
BI Migration & Modernization
Our BI Converter automates approximately 70% of Tableau-to-Power BI migration effort, handling calculation logic, data connections, and visual design translation. This reduces a 12–18 month project to 4–6 months.
Governed Semantic Layers
We build semantic layers (Semantic Edge) that provide consistent business definitions, data quality monitoring, and lineage tracking across the enterprise. This is the foundation for trusted AI.
GxP-Compliant Data Governance
Documented data lineage, quality monitoring, role-based access controls, and audit trails – all designed for GxP, HIPAA, and GDPR compliance from the start.
Who It’s For
Built for life sciences CDOs, data platform, engineering, analytics, and governance teams driving cloud‑native, AI‑ready data modernization.
Results
90%
Processing time improvement, $150K licensing savings, 100+ reports migrated (Snowflake, dbt Cloud, Fivetran, Power BI)
$75K
Annual savings, 40% error reduction via unified manufacturing analytics (Power BI, Power Apps, SQL Server)
Resources
Explore proven strategies, frameworks, and success stories across cloud migration, BI modernization, and compliant analytics in life sciences.
FAQs
How long does a pharma data platform migration take?
Timelines vary by scope, but our Flash Migrate accelerator compresses typical migrations by 20–40%. A full-stack migration (DWH + ETL + BI) for a mid-size analytics environment typically takes 4–8 months.
What is the difference between a data fabric and a data lake?
A data lake stores data in one place. A data fabric creates logical connection layers that provide unified access across multiple systems – without requiring all data to be moved. For pharma, data fabric architectures are often preferred because they respect existing system boundaries and compliance requirements.
Is GxP compliance possible in the cloud?
Yes. All major cloud platforms (AWS, Azure, GCP) support GxP workloads. We design architectures with documented lineage, validated environments, quality monitoring, and audit trails that satisfy GxP requirements.
How does BI Converter work?
BI Converter parses the metadata, logic, and structure of existing Tableau workbooks and translates them to Power BI. It automates approximately 70% of the effort, with expert review handling complex custom visualizations.
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