Enterprise Cloud Data
Warehousing & Lakehouses
We design, build, and optimize enterprise cloud data lakehouses, integrating Snowflake, BigQuery, and Databricks with automated dbt ELT pipelines for sub-second query performance at scale.
Data Warehouse Metrics
Purpose-Built Data Warehousing
Tailored data engineering for cloud lakehouses, automated dbt modeling, and real-time event streaming.
Cloud Data Lakehouse Architecture
Unify structured SQL data and raw un-structured JSON streams into high-performance Snowflake or Databricks lakehouses.
Automated ELT & dbt Data Modeling
Fivetran & dbt pipelines transforming raw data into Kimball Star Schema dimensional data marts.
Real-Time Streaming Data Warehousing
Apache Kafka & Flink real-time event ingestion for sub-second streaming analytics and alert triggers.
Legacy DWH Cloud Migration (Netezza/Teradata)
Migrate legacy on-premise Netezza, Teradata, & Oracle data warehouses to cloud Snowflake / BigQuery.
Data Lake Security & PII Compliance
Role-based access controls (RBAC), column-level encryption, & automated PII masking for GDPR/HIPAA.
FinOps Data Warehouse Cost Tuning
Eliminate runaway cloud warehouse billing by configuring auto-suspend, query caching, & warehouse sizing.
Data Warehousing Practice
From Snowflake data lakehouses to dbt SQL transformations, Kafka streaming, and FinOps cost optimization.
Cloud Data Lakehouse Architecture
Combine the low cost of cloud data lakes with the ACID transaction power of enterprise data warehouses. We design Snowflake, BigQuery, and Databricks architectures built for petabyte scale.
Lakehouse SLA Standards
- 10x query speedup via clustering & columnar compression
- 80% cloud cost reduction via Snowflake auto-suspend
- Zero-copy cloning & dbt data lineage documentation
- 100% intellectual property & dbt code ownership
How We Build Data Warehouses
A structured 6-stage delivery lifecycle from data auditing to dbt modeling, checksum validation, and FinOps cost tuning.
Data Source Audit & Business Requirements
We inspect existing transactional databases, SaaS APIs, file logs, and define target data schemas.
Lakehouse & Dimensional Model Design
Design Snowflake / Databricks data lakehouses using Kimball Star Schema dimensional modeling.
Fivetran & dbt Pipeline Engineering
Configure automated ingestion connectors and dbt transformation models with version-controlled SQL.
Security, RBAC, & PII Masking Setup
Implement role-based access control, dynamic column data masking, and automated data quality checks.
Data Migration & Checksum Validation
Migrate historical data, verifying checksum accuracy between legacy databases and the cloud lakehouse.
FinOps Cost Tuning & 24/7 SLA Support
Establish auto-suspend warehouse policies, executive BI connectivity, and 24/7 pipeline monitoring.
Data Warehousing Tech Stack
Data Warehousing FAQ
Answers to common questions regarding Lakehouses, dbt transformations, and cloud billing controls.
A Data Warehouse stores structured SQL data optimized for BI reporting. A Data Lake stores raw un-structured files (JSON, CSV, logs). A Data Lakehouse (Snowflake / Databricks) combines both, allowing you to query raw files with fast SQL data warehouse performance and low storage costs.
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