Data Warehousing
Data Warehousing: Store. Integrate. Query.
Your analytics demands a robust, scalable foundation. Datafyze builds cloud Data Warehousing and lakehouse architectures, integrating ETL processes, managing storage tiers, and tuning query engines to deliver unified, performant data platforms.
Key Capabilities
Cloud Data Warehouse
Architect solutions on Snowflake, Redshift, BigQuery, or Azure Synapse for scalable, performant querying.
ETL/ELT Integration
Seamlessly load cleansed and enriched data into your warehouse via high-throughput pipelines.
Query Performance Tuning
Implement indexing, clustering, and caching strategies for sub-second query responses at scale.
Data Lakehouse
Combine the flexibility of data lakes with warehouse reliability using platforms like Delta Lake or Apache Iceberg.
Scalable Storage Management
Optimize storage tiers, data partitioning, and lifecycle policies to control costs.
Proven Outcomes
80% faster analytical queries through smart partitioning and indexing.
60% cost savings via optimized storage policies and cold data management.
Unified analytics across structured and semi-structured data in a single platform.
FAQs
Which cloud warehousing platforms do you support?
We support industry-leading platforms including Snowflake, AWS Redshift, Google BigQuery, and Azure Synapse, selecting the best fit based on performance, cost, and existing ecosystem.
What is a data lakehouse?
A data lakehouse combines the scalability and flexibility of a data lake with the performance and structure of a data warehouse providing ACID transactions, schema enforcement, and low-cost storage.
How do you optimize query performance?
We apply partition pruning, clustering, materialized views, and result caching, alongside workload management configurations to ensure consistent low-latency queries, even at high concurrency.