Explain the problem you solved and finish the workshop
Return to the opening situation-room problem and summarize the regional analysis flow and learning outcome.
This step's question
What problem did this workshop solve, and why can you explain the follow-up order?
Return to the opening problem
The situation room received simultaneous requests for Junggye 4-dong, Seongnam-dong, and Junggye Bon-dong. Comparing only patient counts could hide population scale and movement intersections, while looking only at graph connections would not explain the relative priority of the three areas.
The solution is not to declare a high-risk area from one number. You aligned regional names, compared two kinds of population, connected patients, clinics, and hotspots, then made the investigation rule explicit and chose the next follow-up order.
Complete the solution flow
The previous seven stages were not isolated feature exercises. Together they answer one situation-room question.
| Opening problem | Solution applied | Evidence retained | What changed |
|---|---|---|---|
| Regional names from different tables could not be joined safely. | Align them with a composite sido, sigungu, and dong key. | The three region columns in Regional Information | Repeated dong names are not confused across regions. |
| Resident population alone did not describe how many people spend time in the area. | Compare resident and floating population in the same row. | Junggye 4-dong: 7,510 residents and 5,154 floating population | Read living scale separately from movement scale. |
| Patients, clinics, and hotspots were stored in separate datasets. | Connect them to the same dong through ontology entities and relations. | resides_in, located_in, and within | Trace patients, facilities, and routes in one regional context. |
| Aggregates did not show which connections contributed to a result. | Expand the path from a patient to the sido in the graph. | patient → hotspot → dong → sigungu → sido | Explain an observation to the appropriate higher administrative unit. |
| The rule for choosing among three reports was unclear. | Compare patient count, hotspot count, and patients per 10,000 by the same criteria. | Junggye 4-dong and Seongnam-dong each meet 2 signals. | Report the rule and follow-up order together. |
Restate the decision for the three areas
Read this aloud or restate it in your own words.
Junggye 4-dong and Seongnam-dong each meet two investigation signals. Because the current objective is to examine movement intersections, investigate Junggye 4-dong first because it has five hotspots. Check Seongnam-dong second because its 14.22 patients per 10,000 is the largest value, and monitor Junggye Bon-dong under the current rule.
This explanation includes the observed values, applied rule, follow-up order, and limits of the decision. It answers the opening question—where to look first—with traceable evidence.
What you accomplished
- Verified a composite regional key for connecting separate datasets safely.
- Distinguished the questions answered by resident and floating population.
- Connected patients, clinics, and hotspots to the regional hierarchy and traced a path.
- Used aggregate and graph results as different kinds of evidence.
- Applied the same rule to three reports and explained the next follow-up order.
Completion check
- I confirmed that resident and floating population appear in the same Regional Information row.
- I confirmed that patients, clinics, hotspots, and regional relations are connected in the ontology.
- I saw both nodes and edges for the two Cypher queries.
- I compared all three regional results in the table.
- I can explain in my own words why Junggye 4-dong comes first and Seongnam-dong follows.
If an item remains unchecked, return only to that chapter and verify its success condition. You do not need to reread every query and explanation from the beginning.
Apply the method next time
When you apply this workflow to real regional analysis, do not reuse this workshop's numbers as fixed thresholds. Start with these questions:
- Which signal is most directly related to the current investigation objective?
- Could population scale or missing data change the comparison?
- Which evidence and limits should accompany the priority order?
Answering those questions produces an explainable follow-up order for safety inspections, facility placement, commercial-district analysis, and other work that compares several regional reports.
Continue learning
- Extend regional comparisons into dashboard visualizations in the Analyst Path.
- Learn to design entities and relations yourself in the Ontology Modeler Path.