SOURCE: Alpine Data Labs

Alpine Data Labs

November 01, 2011 09:00 ET

Alpine Data Labs Gives Oracle Businesses the Power of Predictive Analytics

Oracle Database Users Now Have the Power of Alpine Miner Version 2.0; Simplicity and Affordability Make It the Product of Choice for Extracting Value From Big Data

SAN MATEO, CA--(Marketwire - Nov 1, 2011) - Oracle database users now have a new tool in their arsenal for extracting value from Big Data with the availability of Alpine Miner Version 2.0 for Oracle. This product expands on the family of predictive analytic solutions from Alpine Data Labs that work within the database itself, giving enterprises a reliable, cost-effective way to apply predictive analytics. Alpine Data Labs also announced today that it will offer connectivity to Netezza later this year and Hadoop in 2012.

Alpine Miner Version 2.0 for Oracle is available for Oracle 11g and Oracle Exadata Database Machine, and comes with all these features and benefits:

  • Support for all data analytics operations, including exploring, transforming, predictive modeling, data mining, scoring, automated model fitting and automated model exporting operations.
  • An intuitive drag-and-drop interface that makes the predictive analytic process straightforward and accessible. Business users and business experts can work side-by-side with analytics experts or use the interface themselves.
  • The fastest end-to-end Big Data Predictive Analytics (BDPA) process. Alpine Miner embeds statistical algorithms in the database to leverage the innate capabilities of peta-scale parallel processing databases.
  • Better model accuracy means better returns, and better use of all data means immediate return on data investments.
  • Scalability enables organizations to use all of their data to develop models, no matter how big their data gets.
  • Reduced risk of dataset leakage because data is analyzed within the database.
  • Facilitates collaboration and the capturing of collective intelligence with libraries and self-documenting workflows to institutionalize the predictive modeling process.

Alpine Data Labs' Alpine Miner is intuitive, affordable and optimized for fast experimentation, collaboration and an ability to work within the database itself -- in short, enabling customers to do incredible things by making it easy and inexpensive to find important insights hidden in massive datasets. With Alpine Miner, predictive analytics moves from being a specialized activity practiced by a few skilled individuals to a vital and highly used competitive tool for modern business. In addition to Oracle 11g and Exadata, Alpine Miner Version 2.0 is available for PostgreSQL and EMC Greenplum.

Supporting Quotes

Anderson Wong, CEO, Alpine Data Labs
"Alpine Data Labs is pleased to extend Alpine Miner to the world's most widely used database. With the availability of Alpine Miner Version 2.0 for Oracle, we've put predictive analytics within reach for thousands of companies. Now Oracle users can get more value from their databases and their Big Data."

David Menninger, Vice President and Research Director, Ventana Research
"Our recent benchmark research on the use of big data shows that over half the participants are performing advanced analyses such as data mining. With the availability of Alpine Miner for Oracle 11g and Exadata, Alpine Data Labs significantly expands its potential customer base enabling more organizations to efficiently unlock the value of their big data."

Links and Resources

Alpine Miner:

Twitter: @alpinedatalabs

About Alpine Data Labs
Alpine Data Labs has developed the first solution for Big Data predictive insight, making it faster, easier and less complex to achieve predictive insights from the massive datasets companies can now collect and store due to declining storage costs. Incubated within Greenplum (acquired by EMC in 2010) and founded by an experienced team with strong ties to China, Alpine Data Labs has Big Data in its DNA. The company is based in Silicon Valley and is backed by Sierra Ventures, Mission Ventures, Sumitomo Corporation and Stanford University.

Contact Information