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Looker Expands Supported Data Warehouses to Now Include Presto and Spark SQL

Analytics 7,700 VIEWS
2/11/2016 9:06:02 AM
Looker Expands Supported Data Warehouses to Now Include Presto and Spark SQL
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Posted Thursday, February 11, 2016 by Richard Harris, Executive Editor


Looker Expands Supported Data Warehouses to Now Include Presto and Spark SQL
Looker has expanded its list of supported data warehouses to now include Presto and Spark SQL, as well as making updates to its support for Impala and Hive. Looker allows enterprises to describe, define and analyze the data where it lives, significantly eliminating the time, expertise, and the cost burdens of moving the data. 

The Looker platform speeds up data analysis in Hadoop and other databases. Data analysts can build a data model across all their data and can describe the data, from metrics to data-definitions, while exposing all of the data, not just a subset. 

Looker’s support of Presto and Spark SQL helps, among others, AWS customers to access all their organizational 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.

Looker facilitates the ability to:


- Leave the data where it is and scale with the cluster

- Build a data model to describe and define data

- Let everyone access and explore the entire data set

For Data Analysts the platform provides:

- A flexible data model for fast iteration and centralized metrics.

- Metrics for fast implementation and best in class analytics.

- A Query Management Panel to kill and optimize queries.

- Model user information and usage across a Looker instance.

- Collaborate, iterate and manage the data model using Git version control software.

Decision Makers can explore all the data - even row level detail providing the ability to:

- Interpret data in seconds with simple, powerful visualizations.

- Create and share dashboards with a link.

- Export to CSV, text, JSON, Excel or Google Docs.

- Flexible scheduling delivers answers to an inbox.

- Run calculations on data with Excel like functionality.

- Get metrics directly from the data analyst.

- Access all data for a 360 degree business view.

Developers can integrate Looker functionality by:

- Easily embedding charts or dashboards in any website, portal or application.

- Connecting and controlling Looker using the available API.

- The Ruby SDK brings query results and charts into existing infrastructure.

- Secure access is available through third-party authentication via LDAP, SAML, Google Apps, and multi-factor authentication.

There is also an entirely white labeled version that provides the ability to build analytic applications and sell it to partners and customers; white label or OEM some or all of the Looker platform into a company’s product; and control the data and analytics exposed with a centralized modeling layer.


READ MORE: http://www.looker.com/product...





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