Executive summary
A leading Managed Service Provider (MSP) operates with a client-first approach to connect businesses with the IT solutions and services required to support sustainable growth in a secured, efficient, and costeffective manner. They offer solutions that address client on-premises, hybrid, and cloud needs, alongside advanced expertise in infrastructure, security, data management, and IT modernization.
Despite a robust operational stack, critical visibility gaps emerged across their financial reporting. To establish a definitive Single Source of Truth, a centralized Data Warehouse and automated ETL framework was implemented to ingest financial data. By integrating critical financial records via APIs, the optimized architecture reclaimed analytical bandwidth, ensuring dynamic cost allocation and delivering comprehensive financial intelligence across the enterprise.
Unified single source of financial truth established
Client overview
To sustain their operations, the organization uses Autotask as their primary PSA tool to automatically track labor, contracts, services, and client tickets, and use Dialpad as their primary call dialer. Furthermore, they utilise QuickBooks as their primary tool for accounting and invoicing needs.
Management ultimately recognized the need for a consolidated approach, as they wanted a 1-stop solution where leadership could securely view, allocate, and analyse their financial KPIs dynamically without relying on siloed data extractions.
Target technology stack
Azure PostgreSQL DB
Custom ETL Framework
Custom Mini Web-App
Power BI Dashboards
Core integrations
QuickBooks (APIs)
Autotask Data Streams
Dialpad Operational Data
Business challenge
Data fragmentation severely restricted the organization’s ability to maintain an agile financial posture. The major challenges that the client faced were primarily due to account management reporting for their financial KPIs and inherent platform limitations.
“Relying on manual heroics to extract intelligence from siloed platforms proved highly inefficient, as base tools did not provide the customized insights or allocation mechanisms required for complex enterprise accounts. ”
Complex Revenue Allocation
The finance team needed a specialized mechanism to accurately allocate invoice amounts related to certain bundled line items to multiple accounts for specific enterprise customers.
Inflexible Cost Distribution
Cost of Goods Sold (COGS) and Expenses from certain accounts had to be shared securely across multiple customers—a functionality that simply isnʼt readily available within standard QuickBooks environments.
Fragmented Visibility
Financial data remained trapped within QuickBooks, operational data in Autotask, and communication logs in Dialpad, preventing a unified, drillable view of comprehensive business health.
Static Reporting Delays
Lacking customized data models, analysts were forced to manually compile static spreadsheets, inherently introducing latency and blocking proactive, daily management of KPIs
Engineering a unified data foundation
To eradicate persistent data silos and manual workflows, a centralized Enterprise Data Warehouse and automated ETL framework was implemented to ingest financial data, establishing an authoritative Single Source of Truth.
Implementation Highlights
API-Based Integration
Engineered robust, automated extraction protocols utilizing APIs to seamlessly and securely ingest raw financial records directly from Quickbooks.
Postgresql Data Warehouse
Provisioned and architected a centralized Postgresql database service via Azure, building a highly scalable foundation for enterprise analytics.
Transformation Logic Automation
Programmatically implemented deep business logic rules to calculate revenue and accurately distribute shared COGs amounts based on specific Revenue % targets.
Revenue Allocation Screen
Deployed a secure mini web-application, giving whitelisted users the direct ability to reallocate amounts from bundled invoice line items dynamically.
Power BI Dashboards
Built an interactive presentation layer enabling complete daily reporting, empowering leadership with granular, drill-down financial insights.
Unified data integration model
The consolidated data platform fundamentally optimized the client’s workflow. Complex logics were integrated to handle constraints that out-of-the-box SaaS tools simply could not manage.
Financial Data Extraction
Direct API connectivity automated the continuous, secure extraction of siloed invoicing, expense, and cost data strictly managed within QuickBooks.
Cost Distribution Pipeline
Engineered transformation layers mathematically distributed shared COGS and Expense pools across multiple customer accounts utilizing strict Revenue % models.
Interactive Web Allocation
A bespoke mini web-application bypassed rigid system constraints, allowing cleared management to fluidly reallocate specific bundled invoice line items.
ETL Automation
A headless framework systematically ingested, cleaned, and organized disparate records, removing the necessity of human compilation or error-prone mapping.
Centralized Repository
The Azure-hosted PostgreSQL data warehouse serves as the bedrock, scaling efficiently to hold millions of secure historical transaction records.
Self-Service Intelligence
Integrated pipelines feed clean, transformed data directly into Power BI, enabling comprehensive self-service analytics without submitting IT requests.
Transformation results
Metric
Before Architecture
After Deployment
Data Integration
Data only available in QuickBooks
Consolidated data in data warehouse for reporting
Data Processing
N/A (Manual Execution)
Automated pipelines
Reporting Speed
Only internal QuickBooks reports available
Ability to create custom dashboards from data warehouse
Executive outcome
“By implementing a centralized and automated data platform, we established an end-to-end automated financial data pipeline from source to insights for Procern and enabled scalable and futur-ready analytics infrastructure. Transitioning from reactive to proactive management, this solution has also empowered stakeholders with sel-service analytics and drill-down capabilities.”
By engineering definitive integrations and custom allocation layers, Procern significantly reduced reliance on static reports and manual data compilation workflows.
Ultimately, this optimization reclaimed vital operational bandwidth and fundamentally improved cross-functional alignment through highly consistent, interactive, and transparent financial reporting views.