Data Hierarchy

Presenting relationships between records to facilitate management of interconnected data.

---

🧩 Overview

Data Hierarchy refers to the organization of data in a parent-child or multi-level structure where records are interlinked and form dependencies. This structure is essential for:

• Representing nested or grouped data
• Maintaining referential integrity
• Enabling recursive querying and cascading operations
• Simplifying complex data relationships visually and structurally

---

🧱 Common Hierarchical Structures

Use Case	Hierarchy Type	Example
Organization Chart	Parent → Child	CEO → Manager → Employee
Product Categories	Multi-level Grouping	Electronics → Phones → Smartphones
Location Management	Country → State → City	USA → California → San Francisco
File Storage Systems	Tree-like Nesting	Folder → Subfolder → File

---

🔄 Data Model Example

Table: departments

id	name	parent_id
1	Corporate	NULL
2	HR	1
3	IT	1
4	Security	3

This model forms a recursive self-referencing hierarchy.

---

🔍 Querying Hierarchical Data

1. Get All Child Nodes of a Department (Recursive CTE - PostgreSQL)

WITH RECURSIVE department_tree AS (
  SELECT id, name, parent_id FROM departments WHERE id = 1
  UNION ALL
  SELECT d.id, d.name, d.parent_id
  FROM departments d
  INNER JOIN department_tree dt ON d.parent_id = dt.id
)
SELECT * FROM department_tree;

2. Build Breadcrumb Path

WITH RECURSIVE path AS (
  SELECT id, name, parent_id, name AS full_path FROM departments WHERE id = 4
  UNION ALL
  SELECT d.id, d.name, d.parent_id, CONCAT(d.name, ' > ', p.full_path)
  FROM departments d
  JOIN path p ON p.parent_id = d.id
)
SELECT full_path FROM path ORDER BY id LIMIT 1;

---

🖼️ UI Representation

• Tree View: Expandable/collapsible nodes
• Breadcrumb: Path navigation (e.g., Home > HR > Payroll)
• Indented Lists: Visually reflect depth using margin
• Graph View: Network-style connected nodes

---

🧠 Best Practices

• Use parent_id columns for self-referencing models
• Ensure proper indexing for recursive queries
• Avoid circular references (parent_id should never loop)
• Limit depth where appropriate for performance and usability
• Consider using closure tables for very deep trees or frequent access

---

🔐 Access Control Use Case

You can use data hierarchy to manage access rights:

Company (Level 1)
├── Region Manager (Level 2)
│   ├── Area Manager (Level 3)
│       └── Agent (Level 4)

Querying upward allows region managers to view data from all their subordinates.

---

🧬 Data Integrity Rules

• A child cannot be its own parent
• Deletion of a parent should either:
  • Cascade delete its children
  • Prevent deletion if children exist
• Prevent orphaned nodes by enforcing foreign key constraints

---

📂 Applications of Data Hierarchy

Domain	Application
HR Systems	Employee hierarchy and reporting
E-Commerce	Product categories and variants
CMS	Nested pages and menus
Finance	Chart of accounts
Logistics	Warehousing and inventory grouping

---

🔚 Summary

The Data Hierarchy workflow helps structure complex interrelated data, enabling logical nesting, efficient querying, and scalable UI/UX design. Whether for org charts, categories, or access control, hierarchies provide essential structure.

---