=====Understanding hub-and-spoke data models: structure and applications=====
By Prawira Denune Galang (dpravira@hse.edu.ru)

====Introduction====

The hub and spoke data model is a popular architecture used for data integration and management in various fields, including business intelligence, data warehousing, and network design. This model is widely adopted because it balances flexibility, scalability, and efficiency. The structure have central hub that serves as the core data repository and spokes that represent different data sources, systems, or data consumers. The hub acts as the mediator, ensuring data consistency and centralization, while the spokes allow for decentralizing data interaction and management. 


====The Structure of the Hub and Spoke Data Model====

the hub-and-spoke model have two main components which is the hub and the spokes.

**The Hub**: The hub serves as the central data repository where data from various sources is collected, cleaned, transformed, and stored. It functions ensuring consistency and accuracy data. Data in the hub can be structured, semi-structured, or unstructured, depending on the organization's needs. The hub not only consolidates data but also applies data governance, security policies, and business rules to ensure that data is managed according to needs. Data stored in the hub can be transformed to meet specific requirements before being distributed to other systems. This centralized storage can take the form of a data warehouse, data lake, or a hybrid, depend on the stakeholders needs. The hub also applies data governance policies such as data quality checks, security measures, and compliance rules.

**The Spokes**: The spokes represent the different data sources that feed data into the hub and the data consumers that extract data from the hub for analysis, reporting, or operational use. These sources can include databases, data lakes, applications, external data feeds, and even IoT devices. The spokes enable data flow between the central hub and various data points, making it easier to integrate diverse datasets. This setup also allows for decentralized data management, where different departments or business units can interact with the data relevant to their functions without impacting other operations.

In the hub-and-spoke model, the hub signifies a central or lead organization that serves as the coordinating entity. The spokes, on the other hand, represent partner organizations that are directly linked to the hub. Each spoke interacts directly with the hub but not necessarily with each other. This structure centralizes decision-making and resource allocation, while also simplifying communication channels. This is comparable to other network structures, like closed networks, where many members interact with one another or open networks, where connections are not common but are still more distributed across partners.

==== Preview comparation between hub-and-spoke and central/decentralized model====

{{:arch:2024:3a.png?600|}}

fig3: Hub and Spokes Model

===Hub and Spokes Model===
a Hybrid model offering agility, standardization and consistency.
In this model the hub is a central analytics team that owns the data platforms and defines the standards and protocols while the "spokes" are the business units that own the data and understand the domains. The "hub" will help implement the data governance processes defined by the spokes and leverage data stewards to ensure consistent business definitions are used.

**Risk**
The hub-and spoke model has a significant disadvantage: the risk of being overly reliant on the central hub. The entire organization could be negatively affected if the hub experiences problems or a breakdown. This vulnerability highlights the importance of robust redundancy and contingency measures.

{{:arch:2024:2a.png?600|}}

fig1: centralized Model

===centralized Model===
A central analytics team serves the data needs for the entire organization across various business units.

**Risks**
bottlenecks/hampers the ability to integrate new datasets, and Business units are unable to get the data-driven insights at the speed needed to support business objectives

{{:arch:2024:1a.png?600|}}

fig2: Decentralized Model

===Decentralized Model===
Separate data teams are assigned to each business unit. Users can create their own datasets without the need for IT to first translate business requirements into technical ones.

**Risks**
Absence of central business definitions and governance processes, Multiple sources of truth that doubt the management's confidence in metrics, and Proliferation of many and incompatible analytics platforms within the organization


====Benefits====
  - **Efficient Communication** :The hub-and spoke model has many advantages, including a streamlined communication process. Information can be efficiently disseminated to all spokes with a central hub as the focal point. This ensures that everyone is on one page. This central communication structure reduces the chance of misinformation, and improves coordination.
  - **Expertise and Specialization** :The hub-and spoke model allows for the creation of specialized departments, or spokes. Each spoke is focused on a specific function or area of expertise. This specialization can lead to greater efficiency and expertise within each spoke, as the team members are able to develop a deeper understanding of their domain.
  - **Clear chain of command** :The hub-and spoke model's centralization establishes an obvious chain of command. The hub is the focal point for decision-making, and provides a framework of governance that is structured. Clarity can help reduce ambiguity and improve accountability. It also allows for quicker responses to problems.
  - **Resource Optimizing**:A hub-and-spoke system can optimize resources, both financial and human, more efficiently. By consolidating certain functions or resource at the hub, economies-of-scale can be achieved. This centralized approach can result in cost savings and better resource allocation.
  - **Scalability**: The hub-and spoke model is scalable by nature. The structure of an organization can grow as new spokes are added. It is ideal for companies that plan to expand or diversify in the future.
====Applications of the Hub-and-Spoke Data Model====
The hub-and-spoke data model has a wide range of applications across industries due to its scalability and efficiency in managing data. Some key applications include:

**Data Warehousing and Business Intelligence (BI)**: The hub serves as a data warehouse where data from multiple sources is consolidated. The spokes represent various data sources such as transactional databases, CRM systems, and external data feeds. The hub enables organizations to check a comprehensive view of their data, while the spokes ensure data is collected from diverse systems. This architecture supports data analysis and reporting, allowing businesses to make data-driven decisions and gain insights into operational performance, customer behavior, and market trends.

**Master Data Management (MDM)**: the hub and spoke model is used to manage an organization master data, which includes critical business entities like customers, products, and suppliers. while The hub acts as the central repository for master data, ensuring a consistent view across the organization. The spokes represent various departments or systems that interact with master data. By using the hub-and-spoke model, organizations can ensure data quality and consistency across multiple business units, and reducing redundancies.

**Network Design and Supply Chain Management**: the hub represents a central distribution center, while the spokes represent various distribution points, retail outlets, or end customers. This model optimizes the flow of goods and services, which is will enabling efficient inventory management and reducing transportation costs. The hub-and-spoke model allows businesses to centralize storage while maintaining flexible distribution routes.

**Cloud Data Architecture**: In a cloud-based hub and spoke setup, the hub is often a cloud data warehouse or data lake that stores data in a central location, while the spokes consist of various cloud services. This approach allows organizations to take advantage of cloud scalability and elasticity while maintaining a consistent and manageable data architecture. It also supports hybrid and multi-cloud strategies by enabling data integration across different cloud environments.

**IoT and Edge Computing**: the hub-and-spoke model can be used to manage data collected from a multitude of connected devices. the hub serves as a centralized platform or cloud service where data is analyzed, while the spokes represent individual or local edge servers. This structure give efficient collection and processing of data at the edge, reducing latency and bandwidth usage by only send a relevant data to the central hub.


====Conclusion====
The hub and spoke data model is a powerful architecture for data management, offering a balanced approach to data centralization and decentralized interaction. Its applications for data warehousing, master data management, cloud architecture, and network design. making this model a versatile choice for organizations for aiming to optimize data management and improve decision making processes. Hub and Spoke distribution systems are particularly useful for any industry that relies on the movement of physical goods through a supply chain


==== References ====
  - The Data Governance Hub and Spoke Model: Why it Works https://solutionsreview.com/data-management/the-data-governance-hub-and-spoke-model-why-it-works/
  - Hub-spoke network topology in Azure https://learn.microsoft.com/en-us/azure/architecture/networking/architecture/hub-spoke?tabs=cli
  - Hub & Spoke Model Reduces Point-to-Point Integration Pain for Enterprises https://www.adeptia.com/blog/eliminate-point-point-integration-pain-hub-spoke-model-enterprises
  - The hub-and-spoke model: An alternative to data mesh https://venturebeat.com/data-infrastructure/the-hub-and-spoke-model-an-alternative-to-data-mesh/
  - The Hub and Spoke Model: How Alteryx Uses Designer Cloud for Product Analytics https://www.alteryx.com/blog/the-hub-and-spoke-model
  - ‘Hub-And-Spoke’: The New Office Model Of The Future, Expert Says https://www.forbes.com/sites/bryanrobinson/2021/06/09/hub-and-spoke-the-new-office-model-of-the-future-expert-says/
  - The Hub And Spoke Distribution Model: Improved Logistics For Nearly Any Business https://www.thebrimichgroup.com/hub-and-spoke-distribution-model/#:~:text=Disadvantages,rotate%20inventory%20among%20several%20locations.