Introduction to BI Tools
BI (Business Intelligence) tools connect to your data warehouse and let you build interactive charts, dashboards, and reports — often without writing any code. They are the final step in the modern data stack, turning warehouse data into business insight.
This lesson is a work in progress. Content will be expanded with hands-on walkthroughs, real dashboard examples, and a video overview.
The BI Tool Landscape
| Tool | Type | Best for |
|---|---|---|
| Metabase | Open source / hosted | Teams wanting quick self-serve analytics |
| Apache Superset | Open source | Technical teams, custom deployments |
| Looker | Commercial | Enterprise, LookML semantic layer |
| Tableau | Commercial | Rich visualizations, large user base |
| Power BI | Commercial | Microsoft / Azure environments |
| Lightdash | Open source | dbt-native metrics layer |
Core Concepts
Connecting to Your Warehouse
All BI tools require a database connection. You'll typically provide:
- Host / account identifier
- Database name and schema
- Authentication credentials (username + password, or service account)
Never store credentials in dashboards or share them across teams — use a read-only service account with access limited to the schemas your BI tool needs.
Chart Types
Choosing the right chart for your data:
| Chart type | Use when |
|---|---|
| Bar / column | Comparing categories |
| Line | Trends over time |
| Scatter | Correlations between two measures |
| Table | Exact values matter, or many dimensions |
| Funnel | Conversion rates through a pipeline |
What's Next
In the next lesson you'll install Metabase locally, connect it to a sample database, and build your first dashboard.