Twitter is upping its data analytics game in the form of an expanded, multiyear partnership with Google Cloud.
With the expanded agreement, Twitter will move its offline analytics, data processing and machine learning workloads to Google’s Data Cloud.
I talked with Sudhir Hasbe, Google Cloud’s director of product management and data analytics, to better understand just what this means. He said the move will give Twitter the ability to analyze data faster as part of its goal to provide a better user experience.
You see, behind every tweet, like and retweet, there is a series of data points that helps Twitter understand things like just how people are using the service, and what type of content they might want to see.
Twitter’s data platform ingests trillions of events, processes hundreds of petabytes of data and runs tens of thousands of jobs on over a dozen clusters daily.
By expanding its partnership with Google, Twitter is essentially adopting the company’s Data Cloud, including BigQuery, Dataflow, BigTable and machine learning (ML) tools to make more sense of, and improve, how Twitter features are used.
Twitter declined a request for an interview but CTO Parag Agrawal said in a written statement that the company’s initial partnership was successful and led to enhanced productivity on the part of its engineering teams.
“Building on this relationship and Google’s technologies will allow us to learn more from our data, move faster and serve more relevant content to the people who use our service every day,” he said.
Google Cloud’s Hasbe believes that organizations like Twitter need a highly scalable analytics platform so they can derive value from all their data collecting. By expanding its partnership with Google, Twitter is able to add significantly more use cases out of its cloud platform.
“Our platform is serverless and we can help organizations, like Twitter, automatically scale up and down,” Hasbe told TechCrunch.
“Twitter can bring massive amounts of data, analyze and get insights without the burden of having to worry about infrastructure or capacity management or how many machines or servers they might need,” he added. “None of that is their problem.”
The shift will also make it easier for Twitter’s data scientists and other similar personnel to build machine learning models and do predictive analytics, according to Hasbe.
On February 2, TC’s Frederic Lardinois reported that while Google Cloud is seeing accelerated revenue growth, its losses are also increasing. This week, Google disclosed operating income/loss for its Google Cloud business unit in its quarterly earnings. Google Cloud lost $5.6 billion in Google’s fiscal year 2020, which ended December 31. That’s on $13 billion of revenue.