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Enterprise supply chain analytics built by someone who understands the business — not just the tools.

Fortune 50 MedTech company — orthopedic surgical robotics & digital enabling technology division

Building a Modern Data Foundation from the Ground Up

Unity Catalog Architecture & Supply Chain Analytics Platform

Supply ChainDatabricksUnity CatalogData EngineeringData Platform ArchitectureTableau CloudSQLPython

Challenge

The business was running its supply chain analytics on SharePoint and Alteryx — a fragile foundation that had accumulated years of technical debt. Broken data lineage, recurring model errors, and zero version control made every planning cycle a liability. There was no single source of truth, no governance structure, and no path to scale without a complete rethink of the data architecture.

Approach

Architected a structured data platform in Databricks purpose-built for supply chain analytics — raw data cleaned, standardized, and made decision-ready with Unity Catalog governance from day one. Automated data ingestion pipelines replaced manual Alteryx workflows, establishing clean lineage and version-controlled transformations. With the foundation in place, BI dashboards were rebuilt on top of governed, reliable data.

Outcome

The impact extended well beyond cleaner dashboards. With trusted data now accessible through Unity Catalog, the team adopted new capabilities like Databricks Genie for natural language querying — and business users voluntarily upskilled their SQL to interface directly with the data. A team that once depended on fragile manual workflows became self-sufficient analytics consumers.

Fortune 50 MedTech company — $27B+ orthopedics division

From Spreadsheets to a Single Source of Truth

Production Sales Inventory (PSI)

Supply ChainDatabricksData EngineeringTableau CloudSQLPythonPSI Reporting

Challenge

Supply chain leaders had no unified view of finished goods and raw materials production, sales, and inventory data. Reporting was fragmented across spreadsheets and legacy systems spanning multiple ERP and planning systems across business units worldwide, making it impossible to align planning decisions at scale.

Approach

Built a unified PSI reporting platform using Databricks as the data warehouse backbone — consolidating and governing data from disparate ERP and planning systems into a single, reliable source of truth. Tableau Cloud was layered on top to transform that consolidated data into role-based dashboards for demand planning, inventory management, and executive review, each tuned to the decisions those audiences actually make.

Outcome

Delivered a production reporting platform used daily by supply chain planning teams across multiple business units. Reduced time-to-insight from days of manual data compilation to real-time access.

Fortune 50 MedTech company — multi-year embedded engagement within a $27B+ orthopedics division

Modernizing Inventory Optimization at Enterprise Scale

Multi Echelon Inventory Optimization (MEIO)

Supply ChainDatabricksData EngineeringTableau CloudCoupaInventory StudioMEIOPython

Challenge

Before a single model could run, the data had to be earned. Inventory inputs spanned multiple ERPs, planning systems, and business files — across both raw material and finished goods networks, each with inconsistent structures and ownership. Solving the ETL challenge was the real work. Layered on top was the need for an analytics framework capable of visualizing model outputs and comparing them against historical baselines so planners could actually trust and act on the recommendations.

Approach

Databricks served as the backbone — consolidating, cleansing, and governing data from every upstream source into a reliable modeling foundation. Tableau Cloud was layered on top to deliver an analytics framework that made MEIO outputs consumable: visualizing safety stock recommendations, surfacing variance against baseline, and giving supply chain planners a clear line of sight from model to decision.

Outcome

Five years of embedded delivery — refining the process through each planning cycle, incorporating discoveries, validating edge cases, and continuously improving model fidelity. What started as a data wrangling challenge became a mature, trusted inventory optimization capability that drove tens of millions of dollars in inventory savings across a global orthopedics supply chain.

Ready to stop guessing and start building?

Whether you're standing up Databricks, rescuing a stalled analytics project, or trying to make your supply chain data actually useful — let's talk.

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