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How a Hub and Spoke Architecture Can Reduce Integration Complexity and Improve Communication

For a lot of business users, the data integration architecture sounds like an oxymoron. That's because they fail to take a possibility into account: data integration may have its own architecture. The reason for this lack of sight is that several data analysts still rely on practices of the 1990s that have become obsolete and limited in capacity with time. 

Truth is, currently, a multitude of data warehouse professionals or integration specialists even now follows the practice of building one independent interface at a time, a poor way to approach a data integration project. And a huge misconception is that switching to a vendor product for data integration automatically assures architecture. 

Here's the catch: If companies fail to embrace the existence of data integration architecture, they can't find out how architecture affects data integration's various aspects: staffing, cost, scalability, and ability to aid real-time, SOA, master data management, and interoperability with integration solutions. 

In this blog, you'll find why data integration needs architecture to make it more independent, future-facing, productive, scalable, and interoperable. Find why hub and spoke architecture is preferred for most integration tools to boot. 

Complexity: Reason Why Data Integration Needs an Architecture

In places where complex data integrations are implemented, the flow of data from myriad source systems (including CRM, supply chain, ERP etc.) through multiple data transformation steps is impacted. Both data sources and targets are heterogeneous in nature. Plus, they have diverse data models. Then particular interfaces uniformly connects these equally diverse pieces. And the data doesn't flow continuously, so companies need data staging areas. These are various reasons why firms need to organize a data integration solution using an architecture.


Role of Data Integration Architecture

Data integration architecture allows companies impose order on the chaos generated by complexity to accomplish certain goals:

Architectural patterns as development standards. Data integration solutions include several components that can be categorized into three broad categories: servers, interfaces, and data transformations. Keeping this in mind, let's explore data integration architecture integration in detail. 

Data integration architecture is a pattern that is constructed when servers relate through interfaces. 

Data integration architecture provides a holistic view of infrastructure and implementations to bolster users by helping them wrap their heads around these with ease. 

Promotes reuse and consistency. As architectural patterns and development standards are implemented in a plethora of data integration projects, the end result is simplicity (as compared to ad hoc methods), which enables the reuse of data integration artifacts (such as interfaces, jobs, routines, and more) - this increases consistency in the handling of data.

Harmony present within the common infrastructure and individual tools. For a data flow or project to be organized in an architecture, the particular infrastructure encompassing integration server and interface must support that architecture. 

Hub and Spoke Architecture Fits the Bill


Hub and spoke architecture is one of the best architectural patterns for data integration. In the hub and spoke model, data transfer and inter-server communication travel through a centralized hub. In this hub, communications are managed and data transformations are performed. This allows it to be cognizant of every transaction, every business activity, every data entry, and more. All this data is compatible as the hub has a job to translate everything into a canonical language. Hence, the hub not only serves as a facilitator of transactions but also companies' window into your business. 

Hub and spoke architecture offers a lot of benefits. Here are a few. 

  1. Enhanced Flexibility: Hub and spoke model includes a flexible architectural pattern that's easy to comprehend and do business with. Not to mention, it can be expressed in a multitude of variations despite its flexibility. 
  2. Increased Reuse: Users typically foster an interface, preferably called spoke, from the hub to a specific system. This interface can be reused for establishing communications among other systems. 
  3. Reduced Interfaces: The ability to reuse interfaces helps users decrease the number of interfaces to be built or maintained. As a result, complexity decreases to a minimum - and agility increases by leaps and bounds. 
  4. Improved Communication: Hub and spoke architecture fosters streamlined communication within the system, allowing users create more sales and ultimately revenue. 

To conclude, hub and spoke architecture allows businesses handle complexity in data integration, promote flexibility and reuse, and improve communication across the business ecosystem for maximized outcomes. 


About the Author

Chandra Shekhar 

Chandra Shekhar is a product marketing enthusiast who likes to talk about business integration and how enterprises can gain a competitive edge by better customer data exchange. He has 8 years of experience in product marketing for SaaS companies.

Published Friday, August 07, 2020 7:52 AM by David Marshall
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