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Documentation Index

Fetch the complete documentation index at: https://docs.datagenie.ai/llms.txt

Use this file to discover all available pages before exploring further.

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What Import and Export is

Scaling your analytics should not mean starting from scratch every time. DataGenie allows you to package your entire dataset configuration into a portable JSON Blueprint for total consistency across every use case. Every KPI definition, dimension assignment, processing preference, and anomaly detection setup is captured in a single lightweight file. Move fast, stay consistent, and eliminate manual errors.

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What the Blueprint contains

KPI Definitions

Every metric you have configured, including SQL expressions and aggregation logic.

Dimension Assignments

The slicing attributes mapped to each KPI for contributor analysis and story generation.

Processing Preferences

Schedule, granularity, thresholds, and anomaly detection group assignments.

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How to export a Blueprint

Open the Dataset Overview screen

Navigate to the dataset you have configured exactly the way you want it and open its Overview screen.

Click Export as JSON

In the top right corner, click Export as JSON. This saves your entire setup into a single portable file.

Save the file

The Blueprint JSON file is downloaded to your machine. Store it wherever your team keeps shared configurations.

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How to import a Blueprint

Navigate to the target dataset

Go to the Datasets screen and open the dataset you want to re-onboard or configure with the same logic.

Click Import Blueprint (JSON)

At the bottom of the sidebar, click Import Blueprint (JSON) and upload your saved file.

Validate and apply

DataGenie instantly populates and validates the entire setup, ensuring your configuration is identical to the original. Review the results and confirm.

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When to use Import and Export

Re-onboarding a dataset

If a dataset needs to be re-processed or rebuilt, import the existing Blueprint instead of reconfiguring from scratch.

Setting up a new dataset with the same logic

When a new dataset shares the same structure as an existing one, import the Blueprint and adjust only what is different.

Sharing configuration across teams

Export a well-configured Blueprint and share it with other teams or workspaces for instant, consistent setup.

Version control and backup

Keep exported Blueprints as a backup of your dataset configuration so you can always restore a known-good state.
Your data logic is now as mobile as you are. Once a Blueprint is exported, it can be imported into any dataset in any workspace, instantly replicating your full configuration with zero manual rework.
After importing, always review the Blueprint sidebar to confirm the populated configuration matches your expectations before activating the dataset.

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What to do next

GO Overview

Back to the full GO onboarding overview.

Complete Workflow

See the end-to-end GO process that produces the Blueprint.

Datasets

Configure and manage your datasets after importing a Blueprint.