Rent Calculator Argentina

Objective

This dashboard helps to adjust rental prices based on Argentina’s inflation index (IPC). Given the country’s high inflation, most rental contracts are updated periodically according to inflation rates. This tool simplifies rent calculations by providing up-to-date indexed values. (I know, you could do this with Excel, Python, or an online tool—I was just experimenting with Power BI a little.)

Scenario

Argentina experiences one of the highest inflation rates in the world. Rental agreements are commonly tied to the inflation index (IPC), requiring frequent recalculations. This dashboard automates the process, ensuring accurate rent adjustments based on official inflation data.

Workflow

1. Data Extraction: The dashboard consumes the IPC data from the BCRA API using a Fabric Notebook (Python).
2. ETL Process: A monthly Fabric pipeline executes the Python script, extracting and transforming the data.
3. Data Storage: The processed data is loaded into Fabric Data Warehouse (DW).
4. Model & Reporting: The Power BI semantic model is refreshed by the Fabric pipeline, ensuring the dashboard always reflects the latest inflation-adjusted rent values.

Key Metrics & Visuals

• Indexed rental price over time based on custom input.
• Monthly and yearly inflation trends.
• User-friendly input fields for rent calculations.

Technologies Used

• ETL: Fabric (Python, Data Factory).
• Data Warehouse: Fabric DW.
• Reporting & Visualization: Power BI.

Impact

• Saves time by automating rent adjustment calculations.
• Provides accurate, real-time inflation-based rent estimates.
• Reduces manual errors in rent adjustments.

Challenges & Solutions

• Data Accuracy: Ensuring data integrity from the BCRA API by validating updates.
• Automation Reliability: Implementing scheduled Fabric pipeline runs to maintain real-time updates.