Star Alliance Airline Soars with Alteryx Server
At a Glance
1000+
Workflows Governed
10
Departments Migrated
25
Alteryx Champions Trained
Overview
Service
Data Engineering & Infrastructure
Industry
Airlines
Stack
Data Engineering & Infrastructure
From Qlik to Databricks: A Governed Lakehouse for a Global Pharma
Author(s)
Scott Carr
Co-Founder & Managing Partner
Technology Stack
The Challenge
A global pharmaceutical company ran its enterprise reporting on roughly 70 Qlik dashboards spanning commercial, marketing, inventory, procurement, logistics, manufacturing, and quality. Underneath them sat more than 1,100 Qlik (QVS) source scripts pulling from QVD files and SQL systems including SAP, Salesforce, and IQVIA. The transformation logic was scattered across those scripts and QVDs with no governed single source of truth, which made reporting slow to change, hard to trust, and dependent on an aging Qlik stack. The client set out to modernize the platform underneath, not just the dashboards on top of it.
The Solution
Compass migrated the client from Qlik to Databricks. We traced each Qlik dashboard back to its source tables, rebuilt the logic as a governed Databricks Platinum layer of 103 curated entities organized into 11 source-aligned domains, and deployed the transformations as PySpark notebooks running on serverless Databricks jobs. Every entity was validated against its original Qlik output before cutover, and the dashboards were rebuilt in Power BI on top of the new Platinum layer, giving the client a modern, governed lakehouse and BI stack whose numbers reconcile to the reports the business already trusted.
Impact
70
Qlik dashboards migrated to Power BI
11
source-aligned business domains consolidated into one governed lakehouse
103
curated Databricks Platinum-layer entities built as the single source of truth
1100+
Qlik (QVS) scripts re-engineered into PySpark on Databricks
Stack
Our Client's Context
The client is a global pharmaceutical company whose reporting had grown up inside Qlik across every major business function — from commercial and marketing to supply chain, manufacturing, and quality. Because the business had run on those Qlik numbers for years, functional parity was a hard requirement: the new platform had to reproduce the existing dashboards exactly. The goal was to retire an aging, hard-to-govern Qlik estate in favor of a scalable Databricks lakehouse and Power BI, without disrupting the reporting the business depended on every day.
Retiring a Sprawling Qlik Estate
Logic Locked in QVDs and QVS Scripts
Reporting logic lived in more than 1,100 Qlik (QVS) scripts and their QVD files, with no governed, centralized model — limiting scalability and making the stack expensive to maintain.
No Single Source of Truth
Data spanned SAP, Salesforce, IQVIA, and other systems across 11 business domains, with definitions duplicated and inconsistent — forcing manual reconciliation before anyone could trust a number.
Parity Was Non-Negotiable
Years of decisions had been made on Qlik numbers, so any replacement platform had to match the old dashboards exactly — dashboard by dashboard, table by table.
One Modern Platform: Databricks + Power BI
Compass ran a systematic, dashboard-by-dashboard migration. Each Qlik dashboard was traced from its QVS scripts back to source tables; those sources were located in Databricks and Unity Catalog, specified as Platinum-layer entities, and rebuilt as PySpark notebooks deployed to serverless Databricks jobs. The result is a governed Platinum layer of 103 entities across 11 source-aligned domains unified by a single conformed date dimension shared across all domain that serves as the blueprint and single source of truth for reporting. Every entity was validated against its Qlik equivalent before go-live, and the dashboards were rebuilt in Power BI on the new layer, all under Unity Catalog governance and Azure DevOps CI/CD.
A Foundation Built to Last: Solution Components and Benefits
Qlik → Databricks Platinum Layer
Compass consolidated the logic behind roughly 70 dashboards, more than 1,100 QVS scripts and their QVD and SQL sources into a governed Databricks Platinum layer of 103 curated entities across 11 domains, deployed as serverless PySpark jobs.
Benefit: A single, governed source of truth replaces scattered QVDs and scripts - one that scales to new sources and workloads without a rebuild, and ends the manual reconciliation that slowed the old stack.
Qlik → Power BI Reporting
The dashboards were rebuilt in Power BI directly on the Platinum layer, each validated for parity against its original Qlik output.
Benefit: Business users get faster, self-service reporting they can trust, with numbers that reconcile to the dashboards they already knew while the client retires its aging Qlik estate.
Validation & Enterprise Governance
The migration was validated dashboard-by-dashboard and entity-by-entity against Qlik, and delivered under Databricks Unity Catalog governance with Azure DevOps CI/CD.
Benefit: A defensible, auditable cutover with business logic that now lives in version-controlled code and governed tables rather than individual Qlik apps, removing key-person risk and giving the client a platform built to last.
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