Task 1 (Data Structure) Task 2 (Terminology standardization) Task 3 (impact of change) Mission 1 (Decision Making) Mission 2 (Exception Scenario) 📊 View Summary ← Classroom
Day 3 Task 01 Data Structure Sorting

Task 01. Resolving differences in data structure understanding (Data Structure Alignment)

Meeting minutes written in natural language are analyzed from a data structure perspective to organize key entities and relationships (Mermaid ERD) to resolve design understanding gaps.

Task 01 Hands-on guide to resolving data structure understanding gaps

📥 Practice Input

  • • day3_meeting_notes.md (meeting minutes)

💾 Practice output (Output)

  • • erd-schema.md (Data Specification and ERD)

1. Story and practice background

Startup planning meeting room. The planner kindly explained the flow, saying, “When a user views an expert’s profile and makes a reservation, the expert can approve or decline, and the reservation is confirmed after payment is completed.” The planner thought of this process as one simple screen flow.

However, in the developer's head Users, Experts, Reservations, Payments Reminiscent of tables, we designed a complex relational model to determine whether they are 1:N or N:M relationships and how status values (Pending, Approved, Paid) interact. If there is a difference in understanding between planners and developers regarding the same service policy, omissions can easily occur at the database design stage, leading to runtime errors or data inconsistencies on the screen.

In this exercise, you will learn how to use Codex to clearly derive entities and relationships from a data structure perspective from planning meeting minutes written in natural language and structure them so that both groups understand the consensus design data model (ERD) without error.

2. Learning objectives

  • Key entities can be logically derived from unstructured meeting records and screen flow descriptions.
  • Relationships and cardinality (1:1, 1:N, N:M) between entities can be clearly defined.
  • The derived relational data structure can be converted to Mermaid ERD and detailed table specifications.
  • The concept design gap (data alignment) between planners and developers can be resolved.

🛠️Practical guide to follow along

  1. Create file for practice: Click the download button below day3_meeting_notes.md file automation/ Save it within the folder.
  2. Codex Review Delegation: Build by sending the **Codex request prompt** below to the Codex Client prompt input window.
  3. Check the relationship model: In the printed statement, review whether the 1:N and 1:1 relationships between User, Expert, Reservation, and Payment, as well as the primary key (PK) and foreign key (FK), are defined as intended.

Download practice materials

Codex request prompt

Task 01 Prompt
Please analyze the provided meeting minutes from a data structure perspective to derive key entities and relationships, and write a data structure definition and Mermaid ERD code.

4. Example results

Codex analyzes the meeting transcript and outputs normalized data entity mappings and a Mermaid ERD script as shown below.

Entity name Description main properties relationship information
User General members using counseling services user_id (PK), email, nickname Reservation and 1:N relationship
Expert Partner experts providing consultation expert_id (PK), name, category Reservation and 1:N relationship
Reservation About user-to-expert reservation mapping reservation_id (PK), user_id (FK), expert_id (FK), status N:1 relationship with User/Expert, 1:1 relationship with Payment
Payment Payment transaction information to confirm your reservation payment_id (PK), reservation_id (FK), amount, status 1:1 relationship with Reservation

5. AI utilization points

  • Entity Inference: Convert physical nouns (properties) and action verbs, which become data storage units in the explanatory text, into relationships.
  • Building the Mermaid schema: Improved collaborative readability by automatically building code for visual materials.