"Looker reinvents the way business intelligence (BI) works by delivering an entirely new kind of data discovery solution that modernizes BI in three important ways. A simplified web-based stack leverages our 100% in-database architecture, so customers can operate on big data and find the last mile of value in the new era of fast analytic databases. An agile development environment enables today’s data rockstars to model the data and create end-user experiences that make sense for each specific business, transforming data on the way out, rather than on the way in. At the same time, a self-service data-discovery experience works the way the web works, empowering business users to drill into and explore very large datasets without ever leaving the browser. As a result, Looker customers enjoy the power of traditional BI at the speed of the web."

"With AWS and Amazon Redshift, Looker customers can build their own modern, big data analytics cloud in just a few clicks. Our data discovery platform was built to take full advantage of the analytical benefits of Redshift. They can explore their entire dataset directly in Redshift; there’s no need to ETL data into a separate data store, cube the data, or re-architect the database for performance. Looker’s 100% in-database approach enables data analysts to build complex models on top of any Redshift data set, transforming data on the fly and building new models from raw data in a matter of minutes. Business decision-makers also reap the benefits of direct data access, as Looker provides browser-based tools for exploration and high-resolution drilling of the entire Redshift dataset."


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Keenan Rice
VP Marketing & Alliances

"Customers deploy the Looker BI platform on EC2 and use any Redshift instance as an analytics infrastructure to provide real-time data access. They manage the live connection to the Redshift instance—or other databases—through the Looker interface, which enables them to model and embellish comprehensive data and perform sophisticated analytics, without needing a star or snowflake schema. At the same time, customer security is never compromised: They can deploy Looker within their AWS Security Group. As business and data needs grow, customers can add resources via AWS to Redshift for scalable, high-performing big data analytics."

“Looker natively supports Amazon Redshift Spectrum, which allows users to analyze exabytes of data stored in S3 without having to load it into Redshift first. Spectrum allows Looker users to dramatically increase the depth and breadth of the data that they are able to analyze in Redshift. Using Looker to join the data in Amazon Redshift with an S3 data lake enables customers to leverage Redshift Spectrum's extensibility and scalability to run sophisticated queries against massive amounts of data inexpensively, in a pay per query manner. Now, the data stored in Redshift and S3, be it structured or unstructured, can be immediately accessed and analyzed together by users of all levels via Looker.”