July 24, 2016 10:47 AM ET

Software

Company Overview of Alpine Data Labs

Company Overview

Alpine Data Labs develops solutions for big data predictive insight. It offers Alpine Miner that simplifies the process of building predictive models for various data sets. The company also provides Alpine Chorus 5.0, an analytics enterprise platform that enables organizations to unify various data access, control, and innovation into one environment. Alpine Data Labs was founded in 2010 and is headquartered in San Mateo, California.

1900 South Norfolk Drive

San Mateo, CA 94403

United States

Founded in 2010

Phone:

650-212-0688

Key Executives for Alpine Data Labs

Chief Executive Officer and President
Co-Founder
Co-Founder and Chief Technology Officer
Chief Product Officer
Vice President of North American Sales
Compensation as of Fiscal Year 2016.

Alpine Data Labs Key Developments

Alpine Data Labs Announces the Introduction of Alpine Chorus 5.0

Alpine Data Labs announced the introduction of Alpine Chorus 5.0, the industry's first Advanced Analytics enterprise platform to enable organizations to unify all data access, control and innovation into one consistent and collaborative environment. With this release, the company introduces new functionality to allow business executives to oversee and manage their analytics ecosystem while enabling all employees to collaborate and innovate with data. Alpine Chorus 5.0 also unveils a new extensible framework which scientists and analysts can use to integrate and manage popular technologies like R and Spark. Finally, the company further advances its 'in-cluster' innovation lead by introducing access, discovery and management parity across all Hadoop distributions (HortonWorks, Cloudera, MapR and Pivotal) and all major database platforms from Oracle, to Teradata to SQL Server. Alpine Chorus 5.0's new monitoring and operationalization capabilities provide all employees with a consistent, personalized and secure interface into the enterprise's analytical work. It ensures that more people, not just data scientists, can actively participate in the development, deployment and fast iteration of insightful applications.

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