OLAP & Data Warehouse Analytics Skill

What problem does it solve?

It helps you choose and design the right OLAP/data-warehouse approach so your dashboards stay fast and maintainable as data volume and complexity grow.

Core Features & Use Cases

• Embeddable OLAP analytics components: Configure and embed interactive reports, charts, pivot tables, parameter forms, and data tables using a shared set of web components.
• Dashboards-ready analytics strategy: Pick the simplest level that works (DuckDB multi-source, DuckDB sync, DuckDB star schema, ClickHouse byte-to-byte, ClickHouse star schema) based on data size and query patterns.
• ETL/architecture planning support: Use replication and denormalization (star schema) concepts to reduce JOIN complexity and improve dashboard responsiveness.
• Practical guidance with real examples: Apply “start simple, scale only when needed” to avoid over-engineering while still planning for higher performance ceilings.

Quick Start

Ask: “Design my OLAP approach for a dashboard—should I start with DuckDB multi-source, then move to DuckDB sync or ClickHouse star schema, and how would I structure the dimensions and facts for my use case?”