Data Warehousing & Business Intelligence
Think of data warehousing like a central pantry—everything is cleaned, organized, and ready to serve up insights when the business needs them.
Definition
Data Warehousing & Business Intelligence (BI) focuses on collecting, organizing, and analyzing data to support reporting, dashboards, and decision-making. It brings together data from across the organization to enable consistent, accessible insights.
- Consolidates data for reporting and analysis
- Enables consistent metrics and trustworthy insights
- Supports dashboards, KPIs, and data-driven decision-making
Core Components
- Data Warehouses & Data Marts
- ETL/ELT Pipelines & Data Modeling
- OLAP Cubes & Semantic Layers
- Self-Service BI Tools & Dashboards
- Performance Optimization & Governance
Example in Practice
An executive team reviews weekly performance metrics in a BI dashboard that draws data from finance, sales, and customer systems—all centralized in a cloud data warehouse. Consistent KPIs and visualizations guide strategic decisions.
Key Techniques & Tools
- Snowflake, Redshift, BigQuery, Azure Synapse
- Power BI, Tableau, Looker, Qlik
- ETL Tools: Fivetran, dbt, Informatica
- Data Catalogs & Semantic Layers
Upcoming Events & Content
December 11, 2025: "From Raw to Refined: Building Trust in BI and Analytics"
Who Should Attend: Analysts, BI developers, data architects, decision-makers
Vendor Partners in this Space
DAMA International (DAMA-I) is a not-for-profit, vendor independent association of technical and business professionals dedicated to advancing the concepts and practices for data resource management and enterprise information. DAMA-I is the parent organization of the DAMA-MN, and has chapters and members throughout the world.