How Digital Transformation Created a Problem Only Composable Analytics Can Solve

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Digital transformation has redefined how we work and connect with each other over the past decade. The last couple of years, in particular, have tested the resilience of businesses of all types and sizes. Enterprises have been under incredible pressure to pivot business models, evolve their product roadmaps, redeploy teams, and engage with customers in radically new ways.

But by disrupting traditional and embedded business processes, the pandemic also accelerated the adoption of new technologies. We become increasingly reliant on digital services every year, and our usage exploded during the pandemic — 64 zettabytes of data came out of 2020 alone, which is nearly as high as the combined total from 2010 – 2016. 

Here’s the problem: Analytics never caught up with the rest of tech innovation and its tsunami of data. Skepticism has kept investments away from analytics and instead towards digital services that output (you guessed it) even more data. This isn’t slowing down any time soon. In fact, IDC predicts that 463 exabytes of data will be created every day by 2025.

The industry is a decade behind, and businesses are starting to feel the burden of data overloads and missed ROI. I call this The Data Problem, and it’s the result of the past 10 years’ biggest area of neglect.

But not all hope is lost. We’ve reached a point where businesses can turn The Data Problem into their biggest area of opportunity. That’s where composability comes into play.

The Future is Composable

Enterprises can avoid drowning in their own data by creating a new, agile infrastructure that brings IT and business together. The composable enterprise puts people at the center of business. This is more than a talent or culture conversation, it’s about having empathy and creating technology that’s more intuitive for the entire workforce.

In today’s age of “data data data!” a composable business approach will break down data silos that can chip away at employee trust and prevent collaboration. More specifically, no-code UI enables employees (technical and non-technical alike) to interact with the data that’s traditionally been a burdensome “IT-only” liability. A recent Gartner presentation predicts that “through 2022, the rapid innovation forced by the COVID-19 outbreak will accelerate the transition of 60 percent of organizations toward composable business and collaborative business-IT continuum.”

Composable enterprise is the future of flexible, resilient businesses. On its surface, it is a dynamic and agile company, able to operate cross functionally and rapidly seize market opportunities. Under the hood, it is a modular approach to solutions able to quickly spin up new applications and connect to new ecosystems quickly and easily. 

Getting to Composability

A composable analytics solution enables anyone to tap into their company’s data fabric and compose new data-driven applications and solutions — no coding experience necessary. There are three core pillars that are vital to creating composable analytics: (1) a headless BI engine, (2) a no-code UI platform, and (3) a broad set of backend integrations that make up the intelligent data fabric of an organization. 

Headless BI:

Traditional, monolithic business intelligence (BI) tools have a fixed set of modules and features. It’s an outdated and inefficient model that drags users away from their workflows, forcing them to toggle back and forth between the BI platform and the actual work environment. A headless engine fixes this problem by exposing a modular set of BI capabilities via APIs — serving as a translation or semantic layer between the company’s data fabric (IT side) and businesspeople (non-technical side). The result is a platform comprised of cloud-based microservices that enable users to work with data in the same environment as their actual day-to-day work.

No-Code UI:

With comprehension and semantics covered by the headless BI, a no-code UI now puts the power of analytics in the hands of business users. It creates analytics building blocks that employees can use to compose their own BI experiences and do more with data.

With composable analytics solutions, The Data Problem no longer seems like such a threat. But there is still a lot of data available, which can be daunting. The bigger the enterprise and its data pool, the greater the need for more analytics and interaction options across a company. No-code UI empowers non-technical employees to enhance their everyday workflows with data and lowers the barrier to data usage throughout their company. It breaks down the barriers in cooperation and coordination between the IT and business teams, allowing for greater innovation and real-time insights — so businesses can make full use of the data at their fingertips. 

Backend integrations:

Finally — The Data Problem not only increased the amount of data available, it also increased the number of sources and types of data formats that make up the full scope of a company’s data fabric. With a no-code UI for use and a headless BI engine to translate, the final piece of the composable puzzle is an extensive series of backend integrations that reliably pull in data from various sources and partners. Trust in data is essential  for enterprises, so backend integrations with data lineage and governance tools provide added protection as more employees work with data.

Yes, we’ve got a huge Data Problem on our hands. But the solution is right in front of us, and it’s the inevitable next generation of enterprises. Composability turns data overload into data power. Analytics is finally catching up to years of digital transformation, so companies can maximize their ROI on data and empower business users — aka, employees like you and me.

About the Author

Roman Stanek is a 20-year veteran of the data industry and world BI expert committed to helping enterprises make the most of their data. Roman founded GoodData on a mission to disrupt the BI space and usher in the new cloud-native era of Data as a Service with enterprise-wide data literacy. As founder and CEO, Roman remains actively involved in GoodData’s client relationships, taking care to understand the specific challenges they face and how data can positively impact a clients’ future success. Throughout his career, Roman has been an outspoken champion of turning data from cost centers into revenue generators.

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