Alpine Predictive Analytics for Greenplum
Data silos and programming requirements deliver slow, less accurate results
Traditional analytics environments are complex programming environments separated from the sources of data, leading to costly data movement, cumbersome model deployment, and all of the errors and delays associated with silos of development. This challenge is multiplied with the information volumes associated with Big Data. Enterprises constrained by the limitations of legacy systems experience a severe disadvantage when attempting to collect accurate and actionable results from predictive models. Extracting data from the source database platform with traditional analytics programs is slow and complex, prompting most enterprises to leverage subsets or samples of the available information. While samples are sufficient in certain contexts, enterprises require a platform capable of delivering accurate, actionable, and timely predictive insight no matter the size or the location of the data.
If your analytics team wrestles with getting access to data, how timely are your insights?
If you are only capable of taking samples, what key trends are you missing? If it takes weeks to deploy analytics workflows, are they still relevant? Are you making incorrect decisions based on an incomplete picture? Are you missing small but highly valuable subsets of your customer base? The choice of what data you want to analyze should be dictated by what is required and what is available, not the limitations of your analytics tool.
The pace of innovation in today’s competitive economy demands answers in real time, not after weeks of analysis. It can take so long to deploy models out of silos, and into operational systems, that analytics projects often become measured in months, revealing insights that are no longer relevant. The best predictions utilize iterative and interactive modeling of the question at hand. However, legacy systems lack the simplicity of an interface designed for business users, resulting in lost productivity for the entire team while updates are made to the model programming.
Predictive Analytics Built for Big Data
The Greenplum Unified Analytics Platform (UAP) combined with Alpine Data Labs delivers deep insights and models from all your data in a simple web-based application that combines the power of big data processing with the sophistication of predictive analytics. This solution moves beyond traditional business intelligence by delivering in-database analytics that allow you to unlock the full potential of your data. More importantly, the platform’s accessible and easy-to-use interface allows everyone on the team to participate in the iterative discovery process.
Greenplum and Alpine Deliver Big Data Predictive Analytics
Combining Alpine’s analytics software for data mining and predictive modeling with Greenplum’s Unified Analytics Platform. Alpine Predictive Analytics for Greenplum delivers an end-to-end Big Data management and computing infrastructure, enabling simple predictive analytics in real time.
Analytics at Scale with No Data Movement
The ability to perform analytics within the source data stores, rather than extracting datasets into separate analytics infrastructures, offers a number of benefits:
- No data movement required
- Built-in scalability from the Greenplum MPP architecture
- One-click model deployment
- A rapid and iterative approach to data modeling
- Elimination of data silos
Enterprise-wide Adoption of Predictive Analytics
With a lightweight installation and an easy-to-use graphical user interface, your entire team — from business users to data scientists — can go beyond traditional reporting to develop predictive models and deliver deep insights.
- Simple to use for every user
- Collaboration between IT, data scientists, business users and analysts
- A single environment for developing and deploying advanced analytics
- Reduces error and lost productivity
- Empowers your entire organization to reveal predictive insights
Greenplum and Alpine transform what has long been a cumbersome, limited, and time-consuming process performed by specialists into a simple workflow that delivers results in real time.
Data Sheet
Product overview of Greenplum Database - massively parallel processing (MPP) database built to support the next generation of “Big Data” warehousing and large-scale analytics processing.
Data Sheet
Greenplum Data Computing Appliance
Product overview of the Greenplum Data Computing Appliance: UAP Edition. The EMC® Greenplum® Data Computing Appliance (DCA) is an integrated analytics platform that accelerates analysis of Big Data assets within a single integrated appliance. Integrating Greenplum Database for analytics-optimzed SQL on structured data, Greenplum HD for Hadoop-based processing of unstructured data and Greenplum partner analytics, BI and ETL applications provides flexibility.
Data Sheet
The world's most powerful distribution of Apache Hadoop. Pivotal HD Enterprise is a commercially-supported distribution of the Apache Hadoop stack including HDFS, MapReduce, Hive, Pig, HBase, Zookeeper, Sqoop and Flume packages from The Apache Foundation.
Whitepaper
Big Data Synergy: EMC Announces Partnership with Alpine Data Labs
In September 2012, EMC Corporation announced that EMC and Alpine Data Labs have expanded their relationship with a formal reseller agreement to combine Alpine Data Labs’ Alpine Miner and Alpine Illuminator predictive analytics applications with EMC’s Greenplum database product line. T
