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Vendia

Joining Analytical Data

Combine datasets from multiple sources to create unified, enriched AI-ready data products. Data joins in Vendia help you build comprehensive, analytical datasets by merging tables from the same or different connected sources.

Important: Data joins require data to be ingested into Vendia tables first, then new combined tables can be created.

Join Capabilities

  • Multiple Join Types: Support for INNER, LEFT, RIGHT, and FULL OUTER joins
  • Cross-Source Joins: Join tables from the same or different connected sources
  • Flexible Interface: Use either the intuitive UI wizard or SQL console for advanced joins
  • Column Control: Select specific columns and apply aliases for clean output

How to Create Data Joins

Vendia provides an intuitive interface for joining tables using either a UI wizard or the SQL console. Follow these steps to combine data from multiple Vendia tables when creating a new Vendia table:

Step 1: Configure Your Join

Select Tables

  • Left Table: Choose your primary table from the dropdown
  • Right Table: Choose the table you want to join with

Choose Join Type

Select the appropriate join type for your use case:

  • INNER JOIN: Returns only matching rows from both tables (most common)
  • LEFT JOIN: Returns all rows from the left table and matching rows from the right table
  • RIGHT JOIN: Returns all rows from the right table and matching rows from the left table
  • FULL OUTER JOIN: Returns all rows when there’s a match in either table

Step 2: Define Join Conditions

Specify how rows should be matched between tables:

  1. Left Table Column: Select the column from your left table
  2. Operator: The join interface uses = for exact matches (for other operators, use the SQL console tab)
  3. Right Table Column: Select the corresponding column from your right table

Example: Join customer tables on email hash

customer_data_a.email_hash = customer_data_b.email_hash

You can add multiple join conditions by clicking “Add Condition” for more complex joins.

Note: For advanced join conditions using operators other than = (such as >, <, LIKE, etc.), use the SQL console tab to write custom SQL queries.

Step 3: Select Output Columns

Choose which columns to include in your results:

  • Return all columns: Include all columns from both tables (prefixed with table names)
  • Select specific columns: Choose only the columns you need for your analysis

Step 4: Preview and Execute

  1. Review your join configuration
  2. Click “Run Query” to execute the join
  3. Preview the results to ensure they meet your expectations
  4. Save the joined table as a new Vendia table for sharing

Join Best Practices

  • Consider data types: Ensure joining columns have compatible data types
  • Start simple: Begin with basic joins and add complexity as needed
  • Validate results: Always preview results to confirm the join logic is correct

Common Join Scenarios

Customer Data Enrichment

Join customer tables from different systems to create a unified customer view:

-- Example: Combine customer data from two different sources
SELECT *
FROM customers_system_a a
INNER JOIN customers_system_b b ON a.email_hash = b.email_hash

Transaction Analysis

Combine transaction data with customer information:

-- Example: Join orders with customer demographics
SELECT c.customer_id, c.age_group, o.total_cost, o.order_date
FROM customer_data c
INNER JOIN order_data o ON c.customer_id = o.customer_id

Regional Insights

Join data across different geographical regions:

-- Example: Combine sales data from different regions
SELECT r1.*, r2.*
FROM region_us r1
FULL OUTER JOIN region_eu r2 ON r1.product_id = r2.product_id

Example Use Cases

  • Create tenant- or customer-specific data products by joining customer data with transaction history
  • Build comprehensive, unified AI-ready data products for analytics by joining data from multiple sources
  • Enrich primary datasets with reference data or lookup tables

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