File Formats
CSV, Parquet, Feather/Arrow, and compressed formats with optimized loading.
Overview
Probably supports the most efficient data formats for fast analysis and visualization. Connect to databases, load files, or generate synthetic data for testing.
Supported Data Sources
Section titled “Supported Data Sources”Database Connections
Direct connections to Snowflake with more database connectors coming soon.
Synthetic Data
AI-generated datasets for testing, prototyping, and learning analysis workflows.
Data Size Capabilities
Section titled “Data Size Capabilities”No Practical Limits
Small Files
Under 100MB load instantly
Large Files
100MB - 10GB optimized loading
Massive Datasets
10GB+ with streaming processing
Getting Your Data Ready
Section titled “Getting Your Data Ready”Data Preparation Tips
Section titled “Data Preparation Tips”- Clean Headers: Ensure column names are descriptive and unique
- Consistent Formats: Use consistent date formats and number formatting
- Missing Values: Probably handles missing data automatically, but clean data works better
- File Encoding: UTF-8 encoding is recommended for international characters
Performance Optimization
Section titled “Performance Optimization”- Use Parquet: Convert large CSVs to Parquet for 10x faster loading
- Index Your Database: Proper indexing dramatically improves query performance
- Filter Early: Use database views to pre-filter large datasets
- Compress Files: Use .gz or .zip compression for faster transfers
Sample Datasets
Section titled “Sample Datasets”Don’t have data to test with? Try these sample datasets:
Sales Sample
Regional sales data with marketing spend, perfect for ROI analysis
Customer Sample
Customer behavior data ideal for churn analysis
What’s Next?
Section titled “What’s Next?”File Formats
Learn about supported file formats and how to optimize file loading performance.
Database Connections
Connect to enterprise databases like Snowflake for real-time analysis.