Looker to Utilize IBM Cloud Data Services to Expand Looker Blocks Ecosystem
By Sara Isenberg
Founder, Publisher, Editor-in-Chief, Santa Cruz Tech Beat
March 29, 2016 — Santa Cruz, CA
[Editor’s note: Santa Cruz Tech Beat previously published Looker Blocks for Google BigQuery, November 11, 2015.]
Looker and IBM to develop ecosystem of Looker Blocks for apps built on IBM Cloud Data Services
Looker announced today that it has formed an alliance with IBM Cloud Data Services to deliver a suite of Looker Blocks, new developer tools designed to simplify and customize data analysis for any business utilizing IBM’s Cloud Data Services.
“IBM is on the forefront of analytics with their investment in Cloud Data Services and Spark. This alliance will enable connectivity between IBM Cloud Data Services and Looker helping customers quickly deploy a full data platform in days,” said Frank Bien, CEO of Looker.
Looker Blocks are templates of common analytic functions which can be assembled and customized to address data needs both company-wide and to any industry-specific requirement. The Looker Block for IBM completes the vision of IBM’s Simple Data Pipe app, utilizing Looker to quickly transform data that has been moved into dashDB using the Simple Data Pipe app.
“IBM is committed to providing developers and builders with the right tools for the job,” said Derek Schoettle, General Manager, IBM Analytics Platform and Cloud Data Services. “By working with Looker and co-developing projects like Simple Data Pipe, we’re delivering on a vision of an open ecosystem where developers can use the tools they want with the support and experience of IBM.”
Looker Blocks establishes a pattern language for analytics and are at the core of what makes Looker different. Looker Blocks make it easy for data analysts to quickly build a data platform with centralized, agreed-upon business logic that every business team can access and use to analyze and answer any question. Looker and Looker Blocks represent a completely new approach to enterprise analytics that is able to meet the needs of both the data analysts and the business user.