Turn Chaos into Actionable Intelligence

A modern data stack is a suite of cloud-native tools focused on automation and scalability. It typically includes a cloud data warehouse (Snowflake/BigQuery), ELT pipelines (Fivetran/Airbyte), transformation tools (dbt), and BI platforms (Looker/Tableau).

Data engineering builds the foundation. Without robust pipelines and clean, structured data (the "engineering" part), your analytics dashboards will be slow, inaccurate, and unreliable. We fix the plumbing so you can trust the water.

A foundation typically takes 4-8 weeks to set up, including ingestion of core data sources and initial modeling. A mature, enterprise-wide data warehouse evolves over 3-6 months as more sources and transformations are added.

Yes, we specialize in migrating data from legacy on-prem databases (SQL Server, Oracle) to modern cloud warehouses. We ensure data integrity, minimized downtime, and improved performance during the transition.

ELT (Extract, Load, Transform) loads raw data into the warehouse first, then transforms it using the warehouse's power. This is faster and more flexible than traditional ETL (Extract, Transform, Load) which transforms data before loading.

For use cases requiring sub-second latency, we implement streaming architectures using Kafka, Confluent, or Kinesis. For most business reporting, "micro-batch" loading (every 15-60 mins) is sufficient and more cost-effective.