Monthly Challenge Solution: July 2026

And that’s a wrap on the July Challenge! 🍉

We loved seeing all the unique approaches this month! Here’s the workflow we built to solve this month's task. There isn’t just one "right" way to build a workflow, so think of this as inspiration rather than the only answer. Check out our solution on the KNIME Community Hub:

Winner announcement is coming soon and a brand-new challenge will drop already soon! Mark your calendars for next Monday!

Solution Summary: We start by reading and cleaning the two datasets: one contains nutrition facts per serving, the other contains local store prices per 100g. After handling missing values and text inconsistencies, we merge the datasets to calculate the protein-per-dollar ratio. From this we identify the top 5 food items that offer the highest protein per dollar.

Next, we calculate the costs per serving. Finally, we create three parallel branches to  pick specific items for a budget-friendly fitness meal:

• a high-protein/low-fat item

• a low-carb item and

• two high-protein/low-calorie vegetables then combine them into a four-item shopping basket.