We specialize in implementing comprehensive data architectures that transform how IT services companies manage and analyze their operational data. Our solutions integrate disparate systems through automated ETL pipelines, creating centralized data warehouses that provide real-time visibility into project health, resource utilization, and client profitability across multiple cloud platforms and technologies.
Design and implement cloud data ecosystems using Azure, AWS, and Google Cloud platforms. Multi-layer architectures with dimensional modeling (star/snowflake schemas) and medallion patterns (Bronze/Silver/Gold). Row-Level Security (RLS) and Role-Based Access Control (RBAC) enforced across all layers for enterprise-grade security.
Automated data pipelines connecting PSA platforms, CRM systems, and billing tools through API integration and database connectivity. Salesforce, Microsoft Dynamics 365, NetSuite, and custom SaaS connectors with Change Data Capture (CDC), incremental loads, and schema mapping logic for seamless data synchronization.
Financial data marts consolidating revenue, expenses, and profitability from accounting systems and payment processors. Multi-source consolidation with automated reconciliation, revenue share calculations, commission tracking, and export-ready datasets for ERP integration.
Specialized business applications for operational workflows including estimation tools, field service management, and data collection systems. Solutions built with .NET, Python, Power Apps, and modern web frameworks. Custom ERP modules and workflow automation tailored to IT services operations.
Enterprise reporting solutions with semantic layers, calculated measures, and security models scaling to 200+ concurrent users. Executive dashboards, operational reports, and self-service analytics with governed data models, automated refresh schedules, and comprehensive monitoring.
Data ingestion using Azure Data Factory, AWS Glue, Google Cloud Dataflow, Python API connectors, and SQL stored procedures. Handles schema drift, pagination, rate limiting, error recovery, and late-arriving dimensions. Slowly Changing Dimension (SCD) implementation, data quality validation, and reconciliation checks for data integrity.
Scalable data warehouse implementations using Azure SQL Database, Snowflake, Google BigQuery, AWS Redshift, and AWS RDS. Platform selection based on performance requirements, cost optimization, and integration needs. Serverless and dedicated resource options for flexible scaling.
Comprehensive security frameworks with encryption at rest and in transit, key vault integration, and audit logging. PHIPA, PIPEDA, and GDPR compliance with conditional access policies, RLS/RBAC enforcement, and Canadian data residency for healthcare and public sector clients.
Azure (Data Factory, SQL Database, Synapse Analytics, Blob Storage), AWS (Redshift, RDS, Glue, S3), Google Cloud (BigQuery, Cloud Storage, Dataflow). Multi-cloud architectures based on performance requirements and cost optimization.
Snowflake, Google BigQuery, Azure SQL Database, AWS Redshift, AWS RDS. Platform selection driven by scalability needs, query performance requirements, and integration complexity.
Power BI (primary platform), Tableau, Looker, Google Data Studio. Enterprise semantic modeling, self-service analytics, mobile reporting, and embedded analytics capabilities.
C# .NET, Python, Power Apps, React, Node.js. Custom applications for specialized workflows, data collection, and operational automation.
Companies like Modern Niagara send out hundreds of proposals and bids each year to prospective customers. This process is often managed manually across multiple spreadsheets, making it difficult to achieve full oversight of the sales funnel. This often translates to a lack of visibility and missed opportunities.
Read More
Complete this form and someone will connect with you within 1-2 business days.
