Case Studies

▸ Challenge

An international energy consulting firm needed a comprehensive system to track global energy commodity movements across multiple countries. Their analysts were spending significant time manually collecting data from disparate sources, leading to delays in critical market analysis.

▸ Solution

We developed a multi-component data platform that automated the entire data collection and distribution process:

• •Automated data feeds from specialized energy commodity APIs
• •Designed and implemented a normalized SQL Server relational database
• •Built a custom Excel VBA application for firm-wide data access with intuitive filtering and export capabilities
• •Created Python-based web scraping and API integration system consolidating national energy statistics from 10+ countries
• •Implemented multi-format data extraction (PDF, DOCX, XLS) with intelligent parsing
• •Custom alerting system for critical market events

▸ Impact

▸ Challenge

A data processing startup needed to scale their document extraction system to handle thousands of documents daily while maintaining accuracy and minimizing processing time. Their existing solution struggled with diverse document formats and couldn't handle peak loads.

▸ Solution

We architected and maintained a cloud-native processing pipeline leveraging the best of Azure and GCP:

• •Hybrid OCR strategy using both Azure and GCP vision APIs for optimal accuracy across document types
• •RabbitMQ-based message queuing system for reliable asynchronous processing
• •High-performance PostgreSQL database design for efficient data retrieval
• •RESTful API delivering sub-second response times
• •Implemented separate web scraping solution for legal data gathering

▸ Impact

▸ Challenge

A mobile app portfolio company was struggling with fragmented data from multiple ad networks, unreliable third-party tools costing thousands monthly, and lack of visibility into data pipeline health. They needed a unified analytics platform to drive decision-making.

▸ Solution

We built a comprehensive data platform on Snowflake and GCP that unified all data sources:

• •Custom alerting framework for Snowflake providing real-time data quality monitoring
• •Automated data feeds integrating major ad networks (Facebook, Google, TikTok, Unity, AppLovin)
• •Marketing spend and revenue reconciliation pipelines ensuring data accuracy
• •Refactored existing data pipelines, identifying and eliminating inefficiencies
• •Replaced expensive third-party tools with in-house solutions
• •Orchestrated with Airflow for reliable, scheduled execution

▸ Impact

▸ Challenge

An enterprise client was operating a 40-year-old DB2 mainframe system that was costly to maintain, difficult to extend, and lacked modern analytics capabilities. They needed a complete modernization strategy that wouldn't disrupt ongoing operations.

▸ Solution

We led a comprehensive cloud migration project delivered in under six months:

• •Architected modern data warehouse using Azure Synapse Analytics
• •Implemented Azure Data Lake for scalable storage layer
• •Designed and executed data migration strategy ensuring zero data loss
• •Built comprehensive data cleansing and validation pipelines
• •Developed Power BI dashboards replacing 100+ legacy reports
• •Phased cutover strategy minimizing business disruption

▸ Impact

▸ Challenge

An energy trading startup needed mission-critical infrastructure to support high-frequency electricity trading operations. The system required real-time data from multiple European energy exchanges with zero tolerance for data loss or delays.

▸ Solution

We designed and built a comprehensive data architecture from the ground up:

• •Architected time-series database solution using TimescaleDB optimized for high-frequency trading data
• •Developed 100+ parallel data pipelines ingesting data from major European energy sources
• •Integrated with ENTSOE (European electricity transmission operators)
• •Connected to JAO (Joint Allocation Office) for cross-border capacity allocation
• •Built redundancy and failover mechanisms ensuring 24/7 availability
• •Implemented sub-minute data freshness for critical trading signals

▸ Impact