Use joins when combining tables from the same database for row-level integration, and use blending when combining data from different sources or when working with pre-aggregated data.
Practical Response 1:
“I use joins when I need to combine tables from the same database for detailed analysis, and blending when I’m working with data from different systems like Excel and SQL Server together.”
Practical Response 2:
“Joins are my first choice for single-source data integration, while blending is perfect for combining data from separate platforms or when I need to bring in supplemental metrics from another system.”
Detailed Explanation:
Joins are ideal when:
- All data resides in the same database or data source
- You need row-level integration with detailed record matching
- Performance optimization through query folding to the database is desired
- You’re working with normalized tables that need to be denormalized
- Complex join conditions (multiple fields, custom logic) are required
Data Blending works better when:
- Data comes from different sources (SQL + Excel, Salesforce + Google Analytics)
- You’re combining data at different levels of granularity
- Primary data source contains the main analysis, and secondary sources provide supplemental metrics
- You need to maintain separate refresh schedules for different data sources
- Working with published data sources on Tableau Server/Cloud
The key distinction is that joins combine data before aggregation (at the row level), while blending aggregates within each data source first, then combines the results.
Keywords:
- joins vs blending Tableau
- data blending vs data joining
- Tableau data combination
- multiple data sources Tableau
- cross-database analysis
When to use Joins vs. Blending in Tableau?