Looker expands analytics to Presto and Spark SQL


Frank Bien, Looker

Business intelligence platform Looker is helping large organisations make better business decisions by expanding its business analytics to work with Presto and Spark SQL, reducing the time, expertise required and cost of moving data before it can be analysed.

Looker’s expansion, which also includes updates for Impala and Hive, enables all members of a business team to access data where it lives, reducing an organisation’s reliance on data scientists and enabling it to transform years of stored data into meaningful and actionable metrics.

“With Looker on Hadoop, data analysts can create a single source of truth for the entire enterprise, so every business team can quickly ask and answer their own questions,” said Frank Bien, CEO, Looker.

The new levels of support also provide complete compatibility with the Amazon Elastic MapReduce (Amazon EMR) suite of frameworks.

“Looker’s support of Presto and Spark SQL helps AWS customers access all their organisational data, whether in Amazon Relational Database Service (Amazon RDS), Amazon Redshift, or, with today’s announcement, in an Amazon Simple Storage Service (Amazon S3) data lake accessed through one of the many SQL engines supported by Amazon EMR,” said Anurag Gupta, vice president, database services, Amazon Web Services, Inc.