Model Bogotá's Bike-Share Network as a Graph for Overnight Rebalancing
Overview
What this challenge is about.
Model Bogotá's Bike-Share Network as a Graph for Overnight Rebalancing. Intermediate challenge in analysis. Analyzing real datasets and building models that ...
The Brief
What you'll do, and what you'll demonstrate.
Decide which overnight truck-route changes will most reduce morning bike and dock shortages, using graph metrics computed from the network's own trip history.
This is not a data exercise. It is the work an analyst does when stakeholders need answers from messy data. That distinction matters to every hiring manager who has seen candidates describe statistical methods and none who have extracted insight from messy, real-world data.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
Earning criteria — what you'll demonstrate
- Translate an operational logistics question into an explicit directed weighted graph schema and defend the modeling choices
- Apply betweenness centrality, constrained shortest-path, and strongly-connected-component analysis correctly and interpret each in plain operational terms
- Combine trip-flow data with station coordinates to produce a geospatial network view that a non-technical reader can act on
- Convert graph metrics into specific, numbered, evidence-backed operational recommendations
- Communicate technical analysis to an operations audience without jargon
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Aligned coursework coming soon.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Graphs
Apply graphs to solve real industry problems and demonstrate production-level capability.
- Networkx
Apply networkx to solve real industry problems and demonstrate production-level capability.
- Shortest Path
Apply shortest path to solve real industry problems and demonstrate production-level capability.
- Centrality Analysis
Apply centrality analysis to solve real industry problems and demonstrate production-level capability.
- Data Storytelling
Apply data storytelling to solve real industry problems and demonstrate production-level capability.
- Geospatial Analysis
Apply geospatial analysis to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Graph / Network Data Engineer
Modeling a real logistics network as a directed weighted graph and computing centrality and component metrics on it is the core daily work of engineers who build routing, recommendation, and fraud-detection systems on graph data.
This challenge sharpens
- graphs
- networkx
- centrality-analysis
Operations Research / Logistics Engineer
Turning constrained shortest-path results into drivable overnight routes mirrors how logistics engineers optimize fleet and dispatch decisions under real time and capacity limits.
This challenge sharpens
- shortest-path
- networkx
- graphs
Analytics Engineer
Packaging network analysis into a map and a memo a non-technical team can act on is exactly how analytics engineers convert raw event data into operational decisions.
This challenge sharpens
- geospatial-analysis
- data-storytelling
- centrality-analysis