Alpine Data Labs announced today the introduction of Alpine Chorus 4.0, the industry’s first Advanced Analytics enterprise platform that enables universal data discovery and search, bi-directional integration between Hadoop and all major data platforms, as well as compatibility with Spark and Cloudera 5.
Alpine Chorus 4.0 brings innovation in data discovery, query parallelization and machine learning in distributed environments. The company also introduces the first of its kind life cycle management facility for Hadoop and non-Hadoop platforms which allows for sophisticated machine learning algorithms to be run and managed simply across heterogeneous data systems such as Cloudera, MapR, Pivotal HD or databases like PostGreSQL, Oracle and Greenplum.
The Network Effect of Insights
“Research shows that only 4% of enterprises get business value out of their Big Data investment” says Joe Otto, President and CEO at Alpine Data Labs. “The current industry solutions encourage a siloed and non-scalable approach to Big Data and that simply limits progress. We focus on building the most comprehensive and scalable platform that enterprises can use to achieve Big Data ROI and to better connect people, data and insights. From helping people quickly visualize and work with any data, to running models 100 times faster on Spark, to operationalizing the deployment of real-time models via standardslike PMML, customers using Alpine Chorus innovate faster because they can easily run deep algorithms at Big Data scale and in a timeframe of businessrelevance.”
The new solution boasts over 100 new features and furthers the company’s advantage in the field of Advanced Analytics. With Alpine Chorus 4.0, data scientists and engineers can be productive on any data – Hadoop or not; business users are engaged early and quickly add value to the advanced analytics conversation; and finally, executives rely on a standard platform to build repeatable, secure and reusable analytical practices.
Over the last 6 months alone, the company has tripled its customer base and has grown by over 200% in the financial services, online media, government, retail and manufacturing sectors.
Data Discovery Made Simple
Most organizations cut into their competitive advantage early in the analytical process because their data scientists can’t easily discover, assemble and transform data before working with it. That process can take months, because moving data is not simple and when it comes to working with Hadoop data, new skillsets need to be acquired.
Alpine Chorus 4.0’s universal data discovery capability allows users to search, find and use data regardless of where it is. Using Alpine Chorus’ “Google-like” search, users can find and browse any file, model, workflow, comment, dataset, etc. – and when data is found, they can visualize it through powerful heat maps, scatter plots and histograms, all without data movement.
“This functionality alone made our team more effective. It allowed us to assemble and understand data quickly, without the complexity of working with MapReduce, or Pig or SQL” says Ron Rasmussen, CTO & SVP Engineering at Xactly Corp. “Our ability to work rapidly and iterate at Big Data scale is core to helping us deliver the best products to our customers.”
Alpine Chorus 4.0 rests on a key new technological breakthroughs:
1) Visualize before You Analyze: Universal Search, Interactive Visualizations and Data Augmentation add a layer of understanding on top of any data.
2) Transform and Query without Extraction: Alpine Chorus comprehensive library of transformation operators – from simple filters, to variable, null-value replacement operators to pivot, multi-join and normalization functions – are accessible via sql editor or visual, drag and drop icons. All of Alpine Chorus operators run in place and in parallel.
3) Manage Data in and out of Hadoop: data can be sent to Hadoop for building Big Data Lakes and out of Hadoop towrite the results of large-scale computation done on Big Data to operational systems.
4) Do Predictive Analytics Natively on Big Data: All of Alpine Chorus are writtenand optimized to execute in parallel, making analysis at Big Data speed a reality.
5) Work with the latest innovations: Embraces Data Science standards for real-time scoring (PMML), as well as supports and contributes to open source platformtechnologies (Spark, Sqoop, Madlib, MLlib, etc). First Advanced Analytics platform to be certified on Spark and Cloudera CDH 5.
6) Extend and Productionize models: Alpine Chorus REST API available to run, and edit run user defined functions (UDFs) as part of an end-to-end analytic workflow.
7) Manage the Analytics Full-Life Cycle: Github-like Version Control (copy workflow, history capture, revert capability), Check-in, commenting, model review andtracking, Job Scheduling, Data management.
“Removing Hadoop’s complexity will give any company a head start, but it’s not enough”, says Steven Hillion, co-founder and Chief Product Officer at Alpine Data Labs. “Once enterprises have identified the data they want to work with, they need to interrogate it without being encumbered by performance issues”.
In this new release, the company unveils its Parallel Analytics Engine, a virtual layer that now executes all of Alpine Chorus’ algorithms with multiple levels of parallelism. This includes the Workflow Graph Optimizer, which parses analytics workloads and deploys them in parallel to maximize the use of available resources; and the Polymorphic Data Service, which decides at run-time how to optimize queries for each type of data platform. These innovations, unique to Alpine Data Labs, represent the most efficient way to run sophisticated machine learning algorithms on a variety of distributed systems. They also made it possible for Alpine Chorus 4.0 to be the first Advanced Analytics platform to be certified on CDH5 and Spark, benchmarked running complex algorithms at up to a hundred times faster than previously possible.
“With Alpine Chorus 4.0 customers can work on important analytical issues at Big Data speed and keep the business engagedbecause of the solution’s visual, powerful and collaborative approach,” says Amr Awadallah, Founder and CTO at Cloudera. “Alpine Chorus is a showcase for analytics innovation in the Big Data Era and we’re excited that it features the power of Cloudera 5.”
The Internet of People
“The key to analytical excellence is collaboration,” says Dan Vesset, Vice President of IDC’s Business Analytics research. “Collaboration often gets a bad name because it sounds too abstract. However, our research shows that effective cross-enterprise collaboration has a determinant role in helping Big Data projects succeed and return value. Alpine Data Labs is leading the way here.”
The new features in Alpine Chorus 4.0 make the benefits of collaboration very tangible:
· Data scientists can tap into the innovation of their business counterparts at every point in the analytics process through user-generated data: comments, tags, links and documents applied to models, workflows, datasets and sandboxes.
· Business Analysts can easily and visually understand data science work through collaborative analytics workspaces, communicating and iterating in real-time, increasing the value and confidence of their analysis.
· Data and IT engineers rely on Github-like version control features, job scheduling and data management capabilities and can operationalize Big Data Analytics in a secure and consistent manner.
· Executives benefit from a platform that is innovative, open and secure because all interactions in Alpine Chorus are recorded and auditable.