Creating Datasets and Data Preparation
A Dataset in Athenic AI is similar to a SQL view which is like a real-time filtered snapshot of data. Each dataset becomes part of the Knowledge Graph, the visual semantic layer that helps Athenic understand your data and respond to natural language questions. For Enterprise Users: Take advantage of 3 hours of complimentary consultation to optimize your datasets, ensuring an optimal experience with Athenic AI.
Prepare Your Data and Understand Datasets
Preparing your data carefully helps build a solid foundation for your AI Analyst and improves the accuracy of insights.
Prepare Your Data
Remove any irrelevant or sensitive columns
Standardize formats where needed (for example, date formats or categories)
Check that relationships between tables are clear and logical
Create Your Datasets
An Advanced Dataset lets you use SQL to:
Define custom metrics, aggregations, or filters
Join multiple tables together with business rules
Clean and reshape data into polished views
Athenic reads your schema automatically, but for advanced datasets you can also manually adjust:
Data types (e.g., number, text, date)
Field names (rename technical names to user-friendly labels)
Column descriptions
This approach is best suited for users comfortable with SQL who want optimized datasets for Athenic AI.
Common SQL Techniques
Join: Combine columns from multiple tables (pre-joining can improve consistency and speed)
Filter: Remove unnecessary rows or columns
Rename: Make column names clearer and business-friendly
Standardize: Normalize values (e.g., “California” → “CA”)
Run and Save Your SQL
Click Run SQL to see a preview
Review the results
Name your dataset (top-left corner)
Click Save
Your saved dataset will appear under Datasets and can be used in your project, added to the Knowledge Graph, and queried using natural language.
Requirements
We highly recommend using a star schema or similar setup for your datasets. If you are not familiar with the concept, here is a great introduction.
Tips for Effective Data Preparation
Use Datasets to apply business logic and create polished views
Select only the tables and fields you need to include in your datasets to keep performance high
Use clear, consistent naming for easier use by your team
Plan your datasets and relationships carefully before creating them
Use joins to prepare your data into the grain you want for your governed metrics.
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