Check your understanding
Data Import workflow
What is the correct order of steps when importing data using the Import tool?
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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
Where are data models saved in Aura, and what does this mean for reuse?
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❏ Models are saved at the instance level and can only be used with that specific instance
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✓ Models are saved at the project level and can be reused across different instances within the project
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❏ Models are saved at the organization level and can be shared across all projects
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❏ Models are saved locally on your computer and must be uploaded each time
Hint
Data models are saved at the project level, which means they can be applied to any instance within that project.
Solution
Models are saved at the project level and can be reused across different instances within the project.
This means you can create a data model once and apply it to multiple instances within the same project, making it easy to maintain consistent graph structures across development, staging, and production environments.
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:
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Finding movies with the same actors
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Discovering actors who worked together
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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.