Cloud News

Why Google Cloud’s Data Analytics Tops The Competition: Debanjan Saha

Donna Goodison

‘We have been in the business of organizing the world‘s information for a very long time,’ said Debanjan Saha, vice president and general manager of data analytics at Google Cloud. ‘Data is in our DNA, and that’s what drives Google.’

Standout Products

Saha called out several Google Cloud products as “best-in-breed” differentiators for its portfolio, including BigQuery, Dataflow, Looker and Cloud Spanner.

BigQuery is Google Cloud’s fully managed, petabyte-scale, multi-cloud analytics data warehouse. It was named a leader in The Forrester Wave for cloud data warehouses in March.

“There is no other cloud data warehouse like that,” Saha said.

BigQuery offers 99.99 percent service-level agreements, which is 10 times better than any other cloud data warehouse, according to Saha.

Google Cloud is working to expand the footprint of BigQuery with BigQuery Omni, which is powered by Anthos, its hybrid and multi-cloud platform. Introduced last July, BigQuery Omni is a multi-cloud analytics solution that allows users to access and securely analyze data across Google Cloud, AWS and Microsoft Azure (in the near future) using standard SQL and without leaving the BigQuery user interface. Now in private alpha, it’s expected to be generally available later this year.

“There are customers…who have data in multiple clouds, and they want to manage it from a single pane of glass and run queries, which crosses cloud boundaries,” Saha said. “For example, we have customers who have data related to their marketing campaigns and ads in GCP and BigQuery, and they’re running some of the applications in AWS. They want to run cross-cloud analytics between data stored in Google Cloud and data in AWS. BigQuery Omni, which is this multi-cloud BigQuery…is going to do that. This is creating essentially a data lake which transcends cloud boundaries.”

Dataflow is Google Cloud’s streaming analytics product designed to minimize latency, processing time and cost through autoscaling and batch processing.

“There is no other product like that,” Saha said. “This is something that we developed to build our ads, stream processing, all the event processing that we do for YouTube and Nest.”

Google Cloud closed its $2.6 billion acquisition of Looker Data Sciences in February 2020, adding its unified enterprise platform for business intelligence, data applications and embedded analytics to its portfolio.

“This is a very modern business intelligence platform, which is very, very different from other options available in the market,” Saha said. “We are very well-integrated with Looker in our portfolio. At the same time, Looker is also a multi-cloud, multi-product platform. BigQuery can be used with Looker, but we also have open interfaces to (Microsoft) Power BI and Tableau, etc. Looker also works with other data warehouses, like (Amazon) Redshift, Snowflake. We believe in an open and multi-cloud environment, and Looker is a perfect example of that.”

Analytics also have underpinnings on databases and storage, and Google Cloud has invested heavily in this area, according to Saha, who noted Cloud Spanner, its fully managed relational database service.

“Those are all very, very special products, and…they offer very different foundational characteristics like security and privacy, scale and performance, availability, etc., which is unmatched in the industry,” Saha said. “We deal with a lot of regulated industries, a lot of compliance regimes, and that is all embedded in our processes and in our products. Those are the foundational aspects where we are much, much better in my view.”