How This Workflow Works
This workflow evaluates the size of an input dataset and automatically chooses between two processing paths: sampling the data if it’s large, or using the full dataset if it’s small. It then creates a bar chart to visualize average working hours by sex, ensuring the process remains efficient and scalable for future data updates.
Key Features:
- Automatically adapts processing steps to the size of the input data
- Ensures efficient visualization by sampling large datasets
- Maintains flexibility for future changes in data volume
- Produces clear visual insights without manual adjustments
Step-by-step:
1. Determine Data Size and Set Branching Condition:
The workflow first checks how many rows are in the input dataset. It then sets a condition to decide whether to process all data or just a sample, based on whether the row count exceeds a defined threshold.
2. Branch Workflow Based on Data Size:
Depending on the result of the size check, the workflow automatically selects one of two paths. For large datasets, it samples a subset of rows to keep processing efficient. For smaller datasets, it uses all available data.
3. Aggregate and Visualize Results:
After processing the appropriate data subset, the workflow creates a bar chart to present data insights in a clear, visual format.