Kai Use Cases & Examples
Practical examples of what you can ask Kai to do.

Troubleshooting
Section titled “Troubleshooting”Debug a failed job:
"Job 789012 failed. Read the error message and identify the root cause."Investigate data quality:
"I'm seeing unexpected nulls in the customer_revenue table. Help me trace where they're coming from."Kai reads actual job logs, checks configurations, and traces data lineage to provide specific solutions.
SQL Transformations
Section titled “SQL Transformations”Create a transformation:
"Create a customer lifetime value model using data from our CRM. First outline the approach, then build it."Convert Python to SQL:
"Convert this Python transformation to SQL for better performance: [paste code]"Complex analytics:
"Build a cohort analysis showing monthly customer retention rates over the past year."Integration Setup
Section titled “Integration Setup”Configure an extractor:
"Set up a Shopify extractor to pull orders, customers, and products."Custom API integration:
"Create a generic extractor for the TikTok Ads API with pagination and OAuth authentication."Add packages:
"Add the pandas package to my Python transformation environment."Create a dashboard:
"Create a sales dashboard with a date picker and bar chart showing monthly revenue by product category."Interactive analytics:
"Build a customer segmentation app that lets users adjust RFM parameters and see segments update in real-time."Documentation
Section titled “Documentation”Generate project docs:
"Generate documentation for the customer analytics flow, including all transformations and their business purpose."Update metadata:
"Generate descriptions for all tables in the customer_data bucket."Data Exploration
Section titled “Data Exploration”Project overview:
"I'm new to this project. Give me an overview of the data structure and what each bucket contains."Business queries:
"Calculate our top 10 customers by revenue for Q3, excluding refunds, and show year-over-year growth."Complex Workflows
Section titled “Complex Workflows”Build a pipeline:
"Build a complete pipeline from Shopify to Snowflake with data quality checks and customer segmentation."Data migration:
"Help me migrate our legacy MySQL analytics to Keboola, preserving all existing business logic."Tips for Better Results
Section titled “Tips for Better Results”| Instead of | Try |
|---|---|
| ”Build a data warehouse” | Break into steps: “First design the dimensional model”, then “Create staging transformations" |
| "Calculate churn rate" | "Calculate monthly churn rate where churned = subscription ended and no renewal within 30 days” |
| One complex request | Iterate: basic version first, then add features incrementally |
For more tips, see Best Practices.