Data & Analytics Technologies
Create trusted data foundations for reporting, operations and AI.
Data architecture should make information discoverable, trustworthy and reusable while matching the scale and latency the business actually needs.
Themes
What this area covers
Selection
Selection criteria
- Volume
- Velocity
- Data quality
- Latency
- Governance
- Skill set
- Cloud ecosystem
- Cost
Technologies
Data & Analytics technologies
Databricks
Data/AI Platform
Unified data and AI platform for lakehouse, analytics and machine learning workloads.
Snowflake
Cloud Data Platform
Cloud data platform for warehousing, analytics, data sharing and AI-ready data workloads.
Apache Kafka
Streaming Platform
Distributed event streaming for real-time data and event-driven architectures.
Apache Spark
Data Processing
Distributed processing engine for large-scale data transformation and analytics.
Power BI
BI Platform
Microsoft business intelligence platform for dashboards, reporting and analysis.
Tableau
BI Platform
Visual analytics platform for interactive dashboards and business exploration.
dbt
Data Tooling
Analytics engineering tooling for modular, tested SQL transformation workflows.
Architecture before stack
Have a stack already—or need help choosing one?
Tell us what you are building, what already exists and the constraints that matter.