UPDATED 15:38 EDT / SEPTEMBER 17 2018

BIG DATA

Google debuts Cloud Inference API for large-scale time series analytics

Google LLC today unveiled Cloud Inference API, a new managed analytics service capable of carrying out hundreds of thousands of queries per second.

The offering is designed for processing time series data, information made up of numerous individual measurements arranged chronologically in the order they’re generated. This method of collating data lends itself to fields such as sales analytics in which it’s helpful to have insight into changes that unfold over an extended time period.

Google has created a purpose-built query language specifically for Cloud Inference API. Users can specify the time windows they’d like to focus on in an analysis, as well as correlate different datasets from the same period. The service lends itself to exploring everything from long-term trends to isolated events such as a single-day spike in foot traffic to stores.

Google said the Cloud Inference API is capable of running queries against upwards of trillions of data points. Even more notably, the service provides the ability to carry out some queries in real time. As Google engineer Emanuel Taropa wrote in a blog post, this is a capability that has historically been difficult companies to implement on their own, especially on a large scale.

“Whether businesses are measuring clicks, queries, or sensor readings, they’re often generating time series or event-driven data. Analyzing this data offers businesses the potential to uncover insights in real time, but oftentimes it also means building a learning system that can scale to millions or even billions of data streams,” Taropa wrote. “For many businesses, this proves to be prohibitively challenging to design.”

There are many use cases that Google could  target with Cloud Inference API’s real-time capabilities. In industrial settings such factories, for example, analyzing sensory measurements from equipment while they’re still fresh can help technicians catch potential problems early. Fast response times are equally essential in areas such as fraud detection. 

One early customer of Cloud Inference API is Snap Inc., which signed a $2 billion cloud contract with Google in 2017. Peter Ciccolo, an engineer with the company, was quoted as saying that the service “promises to replace several custom dataflows with a single system” at Snap.

Cloud Inference API expands Google’s already extensive lineup of analytics services. The company offers a service called Cloud Dataflow that supports both real-time and historical analytics, a managed version of Apache Spark and numerous other solutions geared toward more conventional use cases.

Image: Google

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