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.
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.