Use case 01
When you want a query drafted faster than writing it from scratch.
Data AnalystSQLAdvancedTemplate
Slowly Changing Dimension Query AI Prompt
Slowly Changing Dimension Query is a advanced template for sql. This prompt is meant to generate production-usable SQL for analytical tasks. It gives the AI enough direction to build a query that is not only correct, but also readable, structured, and adapted to the database engine or business question. Use it when you want a query you can review, run, and modify with minimal rework. It is structured as a reusable template, so placeholders can be filled in for a specific table, metric, or business context. The requested output should be comprehensive, methodical, and suitable for expert review or production-style work.
Prompt text
Write a SQL Type 2 Slowly Changing Dimension (SCD) implementation for the dimension table {{dim_table}} in {{database_type}}.
The table structure uses:
- Natural key: {{natural_key}}
- Tracked attributes that trigger a new version: {{tracked_columns}}
- SCD columns to manage: surrogate_key, valid_from, valid_to, is_current
Write:
1. The CREATE TABLE statement with all required columns
2. The MERGE / UPSERT logic to handle: new records, changed records (expire old, insert new), unchanged records
3. A query to retrieve the current version of each record
4. A query to retrieve the historical version valid at a specific point in time: {{as_of_date}}
Add comments explaining the SCD logic at each step.When to use this prompt
Use case 02
When you need SQL that follows a clear analytical structure with comments.
Use case 03
When you are working across different databases and need engine-specific wording.
Use case 04
When you want a reusable query pattern for profiling, retention, funnels, or forecasting inputs.
What the AI should return
The AI should return a complete SQL query or query set that is ready to review and adapt. It should use comments, readable CTE names, and clear formatting so the logic is easy to follow. If assumptions are required, they should be stated briefly before or after the query. The result should be practical enough that an analyst can copy it into their SQL editor with minimal cleanup.
How to use this prompt
1
Open your data context
Load your dataset, notebook, or working environment so the AI can operate on the actual project context.
2
Copy the prompt text
Use the copy button above and paste the prompt into the AI assistant or prompt input area.
3
Review the output critically
Check whether the result matches your data, assumptions, and desired format before moving on.
4
Chain into the next prompt
Once you have the first result, continue deeper with related prompts in SQL.
Frequently asked questions
What does the Slowly Changing Dimension Query prompt do?+
It gives you a structured sql starting point for data analyst work and helps you move faster without starting from a blank page.
Who is this prompt for?+
It is designed for data analyst workflows and marked as advanced, so it works well as a guided starting point for that level of experience.
What type of prompt is this?+
Slowly Changing Dimension Query is a template. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.
Can I use this outside MLJAR Studio?+
Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.
What should I open next?+
Natural next steps from here are Cohort Retention Analysis, Customer Lifetime Value Query, Date Range and Gap Analysis.