GoodData provides a headless BI service for the enterprise
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GoodData this week delivered on its promise to offer an enterprise edition of its headless business intelligence (BI) service. The company’s platform is built on a microservices-based architecture accessible through application programming interfaces (APIs).
The GoodData.CN production platform builds on a previously released community edition to provide organizations with a data analytics platform that uses cloud-native technologies such as the Kubernetes open-source container orchestration engine. to allow it to adapt, said Roman Stanek, CEO of GoodData. VentureBeat.
This latest version of the platform is free for simple production deployments. More complex use cases for self-service analytics and large-scale production deployments with enhanced functionality will be subject to licensing fees.
Most of today’s BI applications date back to monolithic personal productivity applications that require end users to deploy a lot of code, regardless of the function they invoke. A modern microservices architecture allows organizations to programmatically expose a more modular set of functions designed to scale on demand, Stanek said.
This approach is fundamentally more efficient than deploying monolithic BI applications loaded with modules and functionality that no one actually uses, Stanek added. The GoodData.CN production platform exposes these capabilities through a set of APIs that other applications can use, rather than having an end user navigate through a separate user interface (UI). “There is no user interface,” he said.
The pressure to embed analytics into every application is increasing as end users seek to make faster, better, fact-based decisions. Rather than requiring users to move data into a separate application for analysis, the GoodData.CN platform promises to simplify the process of integrating analytics into one application accessible in near real time.
The need to integrate analytics into applications is increasingly pronounced as organizations seek to accelerate several business digital transformation initiatives. Every application is expected to soon include some type of built-in analytics capability that allows end users to make informed decisions in the moment rather than waiting for a business analyst to generate a report, for example.
As microservice-based applications become more widely deployed, the range of features that can be invoked programmatically through APIs will continue to grow steadily. This approach should also have the added benefit of reducing the size of applications, as components that previously required code to be included in the application are now called through APIs.
A microservices-based application also makes it easy to add new features and capabilities to the software by extracting and replacing the containers used to build it. And if a microservice becomes unavailable for some reason, API calls are dynamically redirected to other microservices to provide redundancy.
Independent software vendors like GoodData are leading the charge for microservices, but it’s only a matter of time before more enterprise developers are using microservices that allow organizations to consume software more flexibly. . The challenge, of course, is that microservice-based applications are more difficult to build and support, given all of the dependencies that exist between the APIs being invoked.
In the case of BI, however, the shift to microservices is expected to ultimately lead to increased use of these applications by a larger end-user base invoking headless platforms from any number of applications. Best of all, organizations will arguably have more control over their BI destiny, as switching from one platform to another in case something better becomes available will usually only require replacing a few APIs.
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