Move over, big data. Cloud data is here

For the past five years, the technology industry has been obsessed with big data: How do we keep up with the increasing volumes of data being generated by some companies? Venture capitalists have poured hundreds of millions of dollars into startups tackling the challenges posed by big data. But while our collective focus has been on big data, a second paradigm shift has been brewing that in 2015 will upend the technology industry once again: cloud data.

We’ve seen a dramatic increase in recent years in the number and variety of cloud vendors emerging to deliver services to business customers. Today’s businesses are increasingly turning to these cloud service providers for both core pieces of their infrastructure and easy-to-deploy solutions for a litany of smaller tasks, from event planning to online surveys. The migration to the cloud is in many ways doing to software what the bring-your-own-device movement did to hardware: accelerating adoption of new technologies by businesses while wresting control away from IT departments. As a result, corporate data is becoming decentralized at an unprecedented rate.

In 2014, the reliance of businesses on cloud services began to hit a critical mass, leading to the emergence of the next natural evolution of cloud services: those whose value comes from connecting multiple cloud services together. These services take advantage of cloud data — the increasingly decentralized data that’s locked away in all the disparate cloud services that businesses rely on — in order to deliver their value-added goodness.

Two categories of cloud data services that are already gaining prominence are self-service analytics and rules engines. Self-service analytics services (also known as self-service business intelligence) enable businesses to analyze all of their cloud data. Vendors like DataHero connect directly to popular cloud services so that users can easily create charts and dashboards and perform complex analysis in and across all of the services they rely on. Rules engines like IFTTT (“If this, then that”) and Zapier enable users to have activity in one service trigger actions in another, like having a tweet sent when you reach your daily Fitbit goal. In both cases, the goal is the same: to enable users to be able to work with all of their cloud data, regardless of where it is.

Building solutions that leverage cloud data is not a trivial task, however, and requires new technologies built upon entirely new architectures. Traditional big data systems were designed for a relatively small number of centralized data sources that are accessible through standardized interfaces. Cloud data solutions, by contrast, must connect to a large number of geographically distributed services, each with its own unique proprietary interface and security model. Thus the architectures that worked so well in the past for managing centralized, on-premises data stores simply won’t work for cloud data.

It’s a hard problem to solve, but for further proof that cloud data is about to hit the mainstream, look no further than the data infrastructure startups that are getting funded. Companies like Segment.io, which recently closed a $15 million Series A round, provide developers with a single API that allows them to bring together cloud data from more than 100 services. If technology history has taught us anything, it’s that a robust developer ecosystem is a great predictor of emerging markets.

Big data will still be the largest elephant in the room — pun intended — in 2015, and so it should be. There remains an incredible amount of work to be done to enable data analysts and data scientists to be able to make sense of the increasingly large and complex data generated by some businesses. But 2015 will also be the coming out party for cloud data, as companies large and small come to grips with the notion that much of their data is no longer within their walls, and the demand from business users to easily bring all that data together becomes a critical pain point.

Chris Neumann is chief executive and a cofounder of data visualization startup DataHero. Previously he was the first employee at Aster Data Systems, which Teradata bought in 2011.