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HomeBusiness IntelligenceAPI-First and Headless BI | What You Have to Know

API-First and Headless BI | What You Have to Know


The standard enterprise intelligence (BI) stack is constructed on many years of legacy applied sciences that do not match the brand new wave of information consumption. As organizations transfer from conventional desktop BI to cloud-based options, there’s an evolution by way of structure and the best way analytics is delivered.

The ever-growing variety of information shoppers and use circumstances requires firms to have the ability to present analytics in an agile method – to builders, finish customers, and clients – to assist their quickly altering enterprise wants.

We want new methods to construct analytics to adapt to this new wave of information consumption. By utilizing an API-first strategy and headless BI, we will construct analytics options to share constant information with all shoppers in the best way they need to eat it. Thus, headless BI and API-first analytics platforms are must-haves for firms that need to obtain the flexibleness required by fashionable analytics.

What does API-first imply?

API-first is an strategy to product growth the place APIs are considered as first-class residents. The strategy concentrates on constructing reusable and simply accessible APIs that shopper purposes can use and eat. Historically, firms would first develop the product after which add APIs on high of it. In API-first, this mindset is reversed — APIs are constructed first and positioned on the heart of the product. By doing so, firms be certain that all the things within the product is consumable through APIs.

What’s headless BI?

Headless BI is a newly launched information analytics structure idea to work together and eat metrics within the fashionable information stack. Headless BI is an analytical back-end that makes standardized metrics accessible through APIs, SDKs, and customary protocols. It’s constructed utilizing the API-first strategy permitting all of the analytical definitions and capabilities to be obtainable by well-documented, declarative APIs.

GoodData headless BI visualization
Headless BI ensures that everybody works with the identical constant definitions of metrics.

In conventional BI, the backend (the “physique”) is tightly coupled with the platform’s UI (the “head”). As a result of different instruments can not entry the metrics outlined within the conventional BI, every separate software your finish customers want will need to have their very own metric definitions which they’ll use. In headless BI, the backend and the presentation layer are decoupled, permitting metric definitions to be consumed by any variety of completely different heads — information instruments, ML fashions, and purposes. And since each head accesses the identical supply of metrics, headless BI ensures that everybody in your group — staff, clients, and companions — works with the identical constant definitions no matter what entrance finish they use.

Why do API-first and headless BI matter in analytics?

Presently, firms are dealing with conditions the place constant metrics should be shared and made obtainable for varied purposes and customers — with various ranges of technical expertise — to make higher enterprise choices. However the issue is just not solely making metrics obtainable; firms are additionally struggling to develop analytics options and information purposes in a contemporary approach.

Most analytics platforms are usually not designed to assist software program growth finest practices as a result of we’re not in a position to entry and handle the code we create once we construct analytics with the platforms. API-first analytics adjustments this paradigm by permitting us to learn and write all of the underlying metadata of the platform — in a declarative format — and offering open APIs to automate the continuing supply course of.

Analytics platforms constructed following the API-first strategy and supporting the headless BI use case may help firms with these ache factors and allow customers to be extra productive of their domains. Now, let’s see how API-first and headless BI may help completely different personas succeed of their roles.

Builders

Declarative APIs enable builders to handle and combine their analytics options like every other software supply code. Information groups can combine analytics growth into their CI/CD processes and work in parallel to model, merge, robotically take a look at, and roll out updates and new information merchandise to manufacturing. And since all analytics definitions are consumable through open APIs, they’re straightforward to reuse or repurpose utilizing templates. For instance, when there’s a have to construct a brand new information software, builders can keep away from ranging from scratch by leveraging the analytics they’ve already created.

Visualization of data analytics automation using CI/CD
Declarative APIs enable builders to combine analytics growth into their CI/CD processes.

By serving metrics over APIs, API-first analytics enable builders to take the benefit of the developer instruments and UI frameworks of their alternative when constructing information purposes, portals, and enterprise processes. They don’t have to know learn how to be a part of tables or information units to create metrics as a result of they’ll simply eat the metrics from the headless BI platform and mix them as they should get the end result they require. Thus, they’ll consider coding the wanted interface whereas the platform handles the computations. With open APIs and open supply SDKs (like Python and React), builders can construct customized analytics experiences quicker and develop them as wanted.

Finish customers

Decoupling the analytical backend and the presentation layer permits finish customers — analysts, information scientists, and enterprise customers — to make use of any information software they see as the very best match for the job. Historically, information fashions and metrics needed to be created for every software individually, which is time-consuming and liable to errors. With headless BI, finish customers from completely different groups, departments, and areas can entry and use standardized metric definitions from a single repository and yield right outcomes throughout all the enterprise.

GoodData analytics data model for external data consumers
Make the most of standardized metric definitions throughout your information instruments.

And since the decoupling makes the info stack front-end agnostic, finish customers can improve their information instruments and purposes when wanted. As soon as they establish a necessity to modify from one software to a different — as a result of efficiency points, pricing considerations, or expertise developments — they’ll simply join it to the headless BI platform and proceed analyzing the info with no need information groups to rebuild metrics for them.

How does GoodData slot in?

GoodData, after in-depth analysis and testing, re-engineered its analytics platform to assist the API-first strategy. By opening the platform to be consumed not simply through its personal UI but in addition third occasion interfaces, GoodData strives to fulfill the brand new wave of information consumption necessities.

GoodData’s API-first analytics platform, along with its Headless BI characteristic, allows firms to develop analytics options like every other software program and supply constant analytics to all finish customers and purposes. Because the chief in BI, GoodData offers versatile and customizable options for all finish customers, no matter necessities or technical functionality.

Where GoodData sits in BI ecosystem
Present constant analytics to all finish customers with GoodData.

On the lookout for extra from GoodData?

GoodData invitations you to dive deeper into your journey by brushing up on the dear insights we offer into our merchandise and the enterprise intelligence business at massive. Strive GoodData’s absolutely managed, API-first analytics platform free of charge or learn the next sources in regards to the subject:

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