Customer Details:
Industry: Construction Infrastructure Services
HQ: Houston, Texas
Revenue: $ 250M
Service Delivered: Data Management
Customer Background:
Our customer – a mid-sized infrastructure services company headquartered in Houston, Texas, with annual revenues of ~$250M. The organization operates across multiple infrastructure service domains and relies heavily on data-driven insights to manage operations, reporting, and business decision-making.
Over time, the company had built several analytic reports on a legacy SaaS Field Service Management (FSM) platform. However, as the business grew and reporting requirements became more complex, the legacy platform struggled to support the increasing scale of data and analytical workloads.
To support future growth and improve analytics capabilities, the organization decided to transition toward a modern cloud-based data platform built on Microsoft Azure. The goal was to establish a scalable and future-ready analytics foundation while ensuring minimal disruption to business operations.
Due to urgent reporting needs and scalability challenges, the organization aimed to complete this transformation within an aggressive 90-day timeframe, while simultaneously laying the foundation for a long-term enterprise analytics roadmap.
Their Challenges:
The organization faced multiple challenges while attempting to modernize its analytics and reporting infrastructure.
One of the most critical challenges was the imminent need to migrate from the legacy FSM platform within a tight timeline of less than 90 days, leaving limited time for planning and implementation. Additionally, the legacy environment had minimal documentation and complex data dependencies, creating risks around potential data loss during migration.
The customer was also undertaking its first major cloud initiative, which meant that internal teams had limited experience with cloud architecture, DevOps practices, and modern data governance frameworks.
Operational challenges further complicated the transformation effort. The organization had a mix of on-site and offshore teams, requiring effective coordination and collaboration to maintain project momentum. At the same time, multiple disparate systems and fragmented data sources made it difficult to create a unified analytics platform.
Furthermore, the company’s analytics maturity was still in its early stages, and the existing reporting environment had self-service limitations, making it difficult for business teams to access timely insights.
These challenges made it necessary to design a migration strategy that would not only move existing workloads to the cloud but also establish a future-ready analytics architecture with improved governance, scalability, and cost management.
Our Solution:
To address these challenges, the team designed a structured platform modernization and migration strategy centered around Microsoft Azure. The approach focused on delivering a Minimum Viable Analytics (MVA) platform quickly, while also defining a long-term roadmap for enterprise analytics transformation.
The project began with a discovery phase to assess the existing environment and reverse-engineer current data processes. During this phase, the team analyzed legacy data pipelines, reporting workflows, and system dependencies to understand how business-critical reports were generated.
A hybrid two-week discovery and execution model was adopted to accelerate the initial assessment and define a structured project plan along with a risk register to mitigate migration risks.
Following this, the team implemented a Minimum Viable Solution (MVS) on Microsoft Azure, designed to support immediate reporting requirements while establishing the foundation for future analytics capabilities. Within a 90-day timeframe, the organization successfully migrated its core data workloads to Azure.
As part of this transition, over 30 legacy reports were modernized and migrated to Microsoft Power BI, enabling improved visualization, self-service analytics, and better business accessibility to data.
The solution also introduced key modernization principles, including:
Cloud-first architecture for improved scalability and performance
Centralized cost management to optimize cloud spending
Unified governance and security frameworks for enterprise data management
Additionally, the project defined a long-term analytics blueprint to guide future development. This blueprint included cross-domain data integration strategies, analytics use case prioritization, and governance frameworks to ensure sustainable growth of the company’s analytics capabilities.
The Impact:
The platform modernization initiative delivered significant improvements in the organization’s analytics infrastructure, operational efficiency, and data accessibility.
By successfully completing the migration within the 90-day timeline, the company was able to transition away from its legacy reporting system without disrupting critical business operations.
The implementation of the Azure-based data platform enabled the organization to modernize its analytics environment while improving scalability, governance, and reporting performance.
Key outcomes included:
Successful 90-day migration from legacy FSM platform to Microsoft Azure
Establishment of a Minimum Viable Analytics platform (MVA) on Azure
Modernization of 30+ legacy reports into Power BI dashboards
Creation of a future-ready analytics architecture blueprint
Development of cross-domain data integration strategies
Improved data governance, cost management, and scalability planning
The transformation also enabled business teams to access more reliable, centralized, and scalable analytics capabilities, empowering leadership with better insights for operational and strategic decision-making.
Overall, the initiative positioned the organization with a modern cloud-based data foundation capable of supporting future analytics innovation and business growth.
