Oracle Autonomous Data Warehouse
Self-Managing, Self-Securing, Self-Optimising — Enterprise Analytics Without the DBA Overhead.
Oracle Autonomous Data Warehouse (ADW) is Oracle's fully managed, AI-powered cloud data warehouse — providing enterprise-scale analytical performance with automated tuning, self-managing infrastructure, and native Oracle Analytics Cloud integration. For organisations running Oracle Cloud applications, ADW provides the most direct path to analytics on Oracle data — with pre-built Fusion Analytics Warehouse connectors that eliminate the complex ETL development other platforms require. Tecksight implements and optimises ADW environments that organisations can rely on for their most critical analytical workloads.
45%
Faster analytics platform go-live with ADW vs traditional DW build
80%
Reduction in database administration overhead with ADW self-management
40%
Lower total cost of ownership vs equivalent on-premise data warehouse
20+
Years of Oracle database and analytics platform experience
Services
Our Oracle ADW Services
Implementation
ADW Platform Implementation
Provision, configure, and optimise Oracle ADW environments — covering service sizing, network connectivity, security configuration, data loading patterns, and Oracle Analytics Cloud integration.
Data Loading
Data Migration to ADW
Migrate data from on-premise Oracle databases, legacy data warehouses, flat files, and other sources to Oracle ADW — using Oracle Data Pump, SQL*Loader, Oracle Data Integrator, and cloud data loading services.
Fusion Analytics
Oracle Fusion Analytics Warehouse
Implement Oracle Fusion Analytics Warehouse (FAW) on top of ADW — providing pre-built Oracle Cloud application analytics covering Finance, HR, Supply Chain, and CX with minimal custom ETL development required.
Optimisation
ADW Performance Optimisation
Tune ADW for demanding analytical workloads — covering data model optimisation, query performance tuning, Exadata Smart Scan utilisation, and materialized view strategies that maintain performance as data volumes grow.
Frequently Asked Questions
ADW is optimised for analytical workloads — data warehousing, reporting, BI, and ML — with columnar storage, vectorised query processing, and features optimised for large-scale reads and aggregations. Oracle ATP is optimised for transactional workloads — OLTP applications requiring high concurrency on mixed read/write patterns. Tecksight recommends ADW for analytics and reporting use cases and ATP for operational application databases.
Oracle FAW provides pre-built data pipelines from Oracle Cloud Fusion applications (ERP, HCM, SCM, CX) to Oracle ADW, along with pre-built analytical subject areas and KPIs that align to Oracle's data models. This eliminates months of custom ETL development, data modelling, and metric definition that organisations using other BI platforms must invest in before they can start analysing Oracle application data.
ADW sizing depends on data volumes, query concurrency, and performance SLAs. Tecksight's ADW sizing methodology analyses your current analytical workload profile — query patterns, data volumes, user concurrency, and batch processing requirements — to recommend an initial OCPUs and storage configuration that balances performance against cost. ADW's elastic scaling means the configuration can be adjusted without downtime as requirements change.