Step 9: Run the import
How to do it:
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Click Run import button
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You’ll be prompted to connect to your database
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Enter your Aura instance credentials:
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URI: Your instance connection string (e.g.,
neo4j+s://xxxxx.databases.neo4j.io) -
Username: Usually
neo4j(or your instance ID for Free tier) -
Password: The password you saved when creating the instance
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Click Connect
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Wait for the import to complete—this may take a minute depending on your dataset size
How it works in the background: The Data Importer: 1. Generates optimized Cypher statements from your model 2. Connects to your Aura instance 3. Executes batched inserts (creates nodes first, then relationships) 4. Verifies all data was imported correctly 5. Reports any errors or warnings
The Data Importer processes your CSV data and creates nodes and relationships in your Neo4j instance. After the import completes, you’ll see a summary of what was created.
Step 11: Save your data model
If you need to import more movie data later or recreate the structure in another instance, the saved model lets you reuse the same mapping without rebuilding it.
How to do it:
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Close the import summary window
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You’ll return to the Data Importer main screen
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Your imported data source appears in the list
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Click on the model name field (it may show "Untitled")
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Enter a descriptive name like "Movies Model" or "Movie Recommendation Dataset"
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Click Save
Reusing the model: Load this model later and apply it to new CSV files with the same structure, making it easy to import additional data with the same schema.
Check your understanding
Data Import workflow
What is the correct order of steps when importing data using the Data Importer?
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❏ Create model → Run import → Upload CSV → Connect to database
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❏ Connect to database → Run import → Upload CSV → Create model
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✓ Upload CSV → Create model → Connect to database → Run import
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❏ Create model → Connect to database → Upload CSV → Run import
Hint
First you need data to work with, then you define how that data maps to nodes and relationships, then you connect and execute.
Solution
The correct order is Upload CSV → Create model → Connect to database → Run import.
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Upload CSV - Add your data source file using "New data source"
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Create model - Define nodes (like Person, Movie) and relationships (like ACTED_IN) with their properties
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Connect to database - Select which instance to import into
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Run import - Execute the import and verify the results
Data model reuse
Can you reuse a data model created for one instance on another instance within the same project?
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✓ Yes, models are linked to the project and can be reused for loads on different instances.
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❏ No, models are linked to the instance and cannot be reused.
Hint
Data models are saved at the project level, which means they can be applied to any instance within that project.
Solution
Yes, data models created for one instance can be reused on another instance within the same project. Models are linked to the project, not the instance, allowing flexibility in how they are used across different instances.
Summary
In this lesson, you completed the import process. You:
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Ran the import: Executed the import process and loaded your movie data into Aura
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Verified your results: Checked that nodes and relationships were created correctly
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Saved your model: Preserved the mapping for future imports
The graph structure you created (Person -[:ACTED_IN]→ Movie) enables queries like: * Finding movies with the same actors * Discovering actors who worked together * Identifying similar movies based on shared cast
Connecting to fundamentals:
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Neo4j Fundamentals: You created the graph elements (nodes, relationships, properties, labels) you learned about in that course
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Graph Data Modeling Fundamentals: You applied modeling principles to design your instance model (Movie and Person nodes with ACTED_IN relationships)
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Importing Data Fundamentals: You used the Data Importer tool to transform CSV data into a graph structure, applying import best practices
Key concepts reinforced:
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Nodes represent entities (Movie, Person) with properties (
title,name) -
Relationships represent connections (ACTED_IN) with optional properties (
characters) -
Data preparation ensures clean imports—checking for unique IDs, consistent types, and proper formatting
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Graph modeling determines query performance—a well-designed model makes recommendation queries fast
Data models are saved at the project level and can be reused across different instances.
For more information on the Data Importer, including supported file formats and advanced mapping options, see the Neo4j Aura Import documentation.
In the next lesson, you’ll write Cypher queries to find movie recommendations by traversing the relationships you just created.