Big Data Predictive Analytics Enhanced in Alpine Miner 2.0
Simplicity, affordability let business users efficiently extract value from big data.
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Alpine Data Labs, a “big-data” predictive insight solutions provider, has released Alpine Miner 2.0. The solution makes predictive analytics accessible to businesses who lack the resources and skills required by traditional predictive analytics products.
Alpine Miner’s simplicity and affordability enables enterprises to institutionalize predictive analytics at all organizational levels. With Alpine Miner, enterprises can foster an analytic culture that gives enhances business innovation and agility.
Alpine Miner is designed for customers with fast-growing data needs that want to add new variables to predictive models and gain fresh insights (as opposed to just sampling data) using an affordably priced data-mining solution.
Alpine Data Labs’ Alpine Miner is intuitive, affordable, and optimized for fast experimentation, collaboration, and an ability to work within the database itself -- enabling customers to easily 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.
Key features of Alpine Data Labs’ Alpine Miner include:
- Supports all data analytics operations expected by business users. Alpine Miner supports exploring, transforming, predictive modeling, data mining, scoring, automated model fitting, and automated model exporting operations.
- Affordable. Alpine Miner breaks down the wall between organizations and the predictive power of their data by dramatically lowering the cost and complexity of predictive analytics.
- Intuitive. Alpine Miner’s intuitive drag-and-drop visual interface 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.
- Speed. Alpine Miner embeds statistical algorithms in the database to leverage the innate capabilities of peta-scale parallel processing databases (such as EMC Greenplum) and delivers fast, end-to-end big data predictive analytics (BDPA) process from modeling to scoring to operationalizing. The streamlined workflow enables rapid experimentation and iteration that leads to true innovation. As the analytic workflow is reduced from months to days, business users’ analytic productivity increases.
- Increased ROI. A shorter, simpler BDPA process and sheer processing speed deliver faster business results. Alpine Miner overcomes the BDPA process and execution challenges that exist when using conventional tools and techniques. The ability to use all of the data means more accurate models are possible because the model is not “overfit” to a small sample. Better model accuracy means better returns, and better use of all data mean immediate return on data investments.
- Completely scalable. Organizations can use all of their data to develop models, no matter how big their data gets.
- Secure. Analyzing the data within the database reduces the risk of dataset leakage from the data warehouse.
- Transformative. Alpine Miner facilitates collaboration and the capturing of collective intelligence with libraries and self-documenting workflows. It enables business users throughout an organization to institutionalize the predictive modeling process and become truly data-driven.
More information is available at www.alpinedatalabs.com.