Data Analytics and Big Data Solutions
Enterprise data platforms spanning data warehouse architecture, real-time stream processing, business intelligence visualization, and advanced analytics modeling.
Overview
We build data platforms that transform raw operational data into strategic business intelligence. Our architectures implement the modern data stack — cloud-native warehouses, ELT pipelines with transformation-as-code, semantic layers for consistent metric definitions, and self-service visualization tools that democratize data access across organizations. We handle the full spectrum from batch processing of historical datasets to real-time stream analytics that power operational dashboards and automated alerting systems.
Core Capabilities
Data Warehouse Architecture
Snowflake, BigQuery, and Redshift implementations with dimensional modeling and incremental refresh strategies.
Pipeline Engineering
ELT pipelines with dbt for transformation, Airflow for orchestration, and data quality validation gates.
Real-Time Analytics
Stream processing with Kafka and Spark Streaming for operational dashboards and event-driven alerting.
BI & Visualization
Tableau, Looker, and custom dashboard development with governed semantic layers and row-level security.
Engineering Process
Data Strategy
Source system inventory, data quality assessment, and analytics use case prioritization with stakeholders.
Architecture Design
Warehouse modeling, pipeline topology design, and governance framework establishment.
Pipeline Development
Source connector implementation, transformation logic, and data quality test suite development.
Analytics Activation
Dashboard development, metric layer definition, and self-service training for business users.
Architecture Highlights
Medallion architecture with bronze, silver, and gold data layers for progressive data refinement
Real-time customer 360 profile combining behavioral, transactional, and demographic data streams
Data mesh implementation enabling domain teams to own and publish data products autonomously
Automated data lineage tracking providing impact analysis for upstream schema changes
Ideal Use Cases
Marketing attribution modeling across online and offline channels
Financial reporting automation with regulatory compliance
Supply chain analytics with demand sensing and inventory optimization
Customer churn prediction with proactive retention campaign triggers