Comprehensive Solutions
From ingestion to insight — build robust data systems that scale with your business.
Data doesn’t live in isolation. We take a systems-thinking approach to build reliable, modular pipelines and platforms across the full lifecycle.
- Ingestion: Ingest data using Snowpipe (Snowflake), Kinesis (AWS), Pub/Sub (GCP), or batch with Spark and Airflow.
- Storage: Optimize schema design across Snowflake, Redshift, PostgreSQL, and NoSQL like DynamoDB or Aurora.
- Processing: Build and orchestrate ETL/ELT flows with dbt and Airflow. Use PySpark for distributed processing.
- Analytics: Enable high-performance BI with Looker, Power BI, or Tableau using star/snowflake schemas and semantic models.
- ML Infrastructure: Enable ML pipelines with Vertex AI, SageMaker, or Databricks ML — including feature stores and versioned training datasets.
- Governance & QA: Implement column-level lineage, role-based access, data quality checks, and automated tests.
Need to unify your data workflows? We’ll architect it right from the start.