Data is one of the most valuable assets companies have. They use it for everything, from connecting with customers to identifying new products to introduce and modifying business practices. Data structures are essential to companies maximizing their data functions while maintaining data integrity and keeping up with real-time changes.
The hierarchical structure is one of the more popular data model types. So, what is a data hierarchy? What are the benefits of hierarchical data models? We’ll cover those questions and more in this short article.
What is a hierarchical database?
A hierarchical database is a data model based on a system of hierarchy. This hierarchy is a tree-like structure that stems from a root node, also known as a parent node. The nodes that stem from the root of the tree structure are child nodes. Each node contains one value.
A child node can only have one parent node, but a parent record can have multiple child records. A prime example would be a database model of a corporate structure. The CEO would be the root node, and other executives would branch off from the CEO. Each of those execs could become a parent node and “give birth” to other child nodes that represent administrators who report directly to executives. This parent and child family tree would continue to grow and branch off until reaching the entry-level people at the bottom of the tree.
What is a relational database?
Relational databases are the most common data structure. They use rows and columns to group related data and implement concrete master data. This data model is valuable due to the high level of data integrity it provides. When a value is changed in a field in a relational database, those changes transcend channels, ensuring the data is the same across all platforms.
One of the drawbacks of the relational model is they’re not ideal for inputting large amounts of data. However, they’re perfect when the master data is one of the most important features in the database.
What is the root node?
The root node in a hierarchical model is the node from which all others flow. You could think of it as the master data in the database. Each of its descendants is a parent node and represents a different possibility. A simpler way of putting it is the root node is the node that all others answer to in the hierarchy.
What are parent and child nodes?
A parent node is the child (or descendant) of a root node. Once again, we’ll use a corporate structure as a model. A company’s president would be its root. The vice president would be a parent record as it would have child records below it that report to it.
A child node is a node that stems from (or reports to) a parent record or node. The parent-child is like that of a family tree with the root being a grandparent, the parent records being its direct descendants, their children, and so on.
What are some common use cases of hierarchical database models?
There are some great advantages to hierarchical databases. As you’ve seen in this article, they’re great for detailing corporate structures. However, they’re also great for creating arrays for data analytics projects. They’re also great for creating workflows for data integration processes like ETL and data virtualization. Indeed, there are countless use cases for hierarchical data models.
Hierarchical database models are simpler than they sound if you’ve never heard of one. They’re simply a type of database that employs a tree-like structure. It has some advantages over relational databases and plenty of real-world use cases. It’s a great file system for eliminating data redundancy and creating analytics models. Indeed, hierarchical database models play a vital role in data science and many other fields of endeavor.