Sparx EA and Open Collaboration

By Tim Ackroyd on

I get asked, quite often, "Is there a way to integrate Sparx Enterprise Architect (EA) with other tooling?"

My answer is always, "Yes".

There are multiple approaches, from very simple to more advanced. I have helped several shops do this over the years, and may do videos on this in the future.

Integrating Sparx with Azure DevOps and other Cloud platforms, as well as other Tooling, is very possible and beneficial for managing delivery, such as requirements, problem solving, design, and development... all in a unified way. 

The integration can allow companies/shops to seamlessly synchronize between Sparx EA's modeling environment and platforms, such as Azure DevOps'.

Remember that one of the biggest benefits of Sparx EA over other modeling platforms, is that Sparx is based on Data-First implementation and supports open integration.

Years ago, something call Open Services for Lifecycle Collaboration (OSLC) came out and Sparx was one of the first to embrace it. A good starting reference is, OSLC Architecture Management 2.0 

Today, we develop our own extracts of Sparx data and ingest into Microsoft's ADLSg2. We mine the Sparx data, along with a plethora of other data for intelligence purposes (general analytics and advanced analytics/ML). Our objectives are to understand all data relevance, both horizontally and vertically.

As for Kanban boards, we can use Sparx Kanban and if other platforms support open data collection, we can use their Kanban implementations. For example, we can integrate with other ALM/DLC tooling to ingest their data for use in Sparx EA. For example, Requirements developed in Microsoft Office products (e.g., Excel or Word) or Atlassian's Jira, then ingest data to build elements in Sparx EA.

We tend to look for platforms that are "open" and allow us to use "our data" anyway we desire. Sparx EA is one of those tools. Others are black box and do not allow for such open connectivity.

I could talk about this subject for hours and days, but will stop here. We will dive into this subject more, in our Channel, UML Operator, later.

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