In this tutorial, you'll create a complete data workflow using Build Studio — from raw Excel input to a polished summary report. No coding experience needed. You'll describe what you want in plain English, and Dittah's AI will generate the code.
What You'll Build
A workflow that takes a monthly sales Excel file, calculates key metrics (total revenue, top products, regional breakdown), and generates a formatted summary report.
Time required: ~10 minutes
Step 1: Open Build Studio
Log in to Dittah Studio and click Build Studio in the left sidebar. Click New Workflow to start fresh.
You'll see the workflow canvas — a blank slate where you describe your automation.
Step 2: Describe Your Input
In the prompt area, describe your data source:
"I have a monthly sales report in Excel format. Each row has: date, product name, region, quantity sold, and unit price."
Dittah will ask clarifying questions if needed, or directly generate the ingestion step. You can also upload a sample file so the AI can inspect the actual structure.
Step 3: Describe the Transformation
Now tell Dittah what you want to calculate:
"Calculate total revenue per product and per region. Find the top 5 products by revenue. Show month-over-month growth percentage."
The AI generates Python code that performs these calculations. You can see the generated code, but you don't need to understand it — the preview output shows you exactly what the result looks like.
Step 4: Preview and Iterate
Click Run Preview to execute the workflow with your sample data. You'll see:
- A table with revenue by product and region
- The top 5 products ranked by revenue
- Growth percentages compared to the prior month
Not quite right? Just refine your description. For example:
"Also exclude any rows where quantity is zero. And round all percentages to one decimal place."
Dittah regenerates the code. Preview again until the output matches your expectations.
Step 5: Add an Output
Decide where the results should go:
"Export the summary as an Excel file with two sheets — one for the regional breakdown and one for the top products. Also send a brief email summary to the team."
Dittah adds output steps for file generation and email delivery. You configure the email recipients in the workflow settings.
Step 6: Freeze and Publish
When you're satisfied with the output, click Freeze. This locks the generated Python code — from this point on, no AI is involved in execution. The frozen code runs deterministically: same input, same output, every time.
Click Publish to make the workflow available. You can:
- Run on demand — trigger manually from the Ops Hub
- Schedule — run daily, weekly, or monthly on a cron schedule
- Trigger via API — call the workflow from an external system
What Happened Behind the Scenes
Here's what makes this different from other AI tools:
- AI designed the workflow — it understood your intent and generated clean Python code
- You tested and approved it — the preview let you verify before committing
- The frozen code runs without AI — no LLM calls at runtime, no hallucination risk, no variable outputs
- Every execution is auditable — Ops Hub logs inputs, outputs, and timing for every run
This is the Dittah philosophy: AI builds, code runs.
Next Steps
- Getting Started guide — if you haven't set up your environment yet
- Build Studio deep dive — explore all the capabilities
- Understanding Data Fences — set up access control for your team (coming soon)
