Datawatch Angoss Simplifies Data Science and Analytic Tasks on the Apache Spark Platform
Knowledge STUDIO for Apache Spark Provides Scalable Data Analysis Across Large and Small Data Sets to Build Analytic Workflows Without Complex Coding or Scripting
Datawatch Corporation announced the general availability of Datawatch Angoss Knowledge STUDIO for Apache Spark, enabling organizations to act more confidently with their data and rely on consistent, trustful results in making better business decisions. In combination with its market-leading data visualization approach for building, exploring and segmenting data using patented Decision Tree technology, Datawatch Angoss enables data science teams to create predictive analytic models using Apache Spark by means of a drag-and-drop / point-and-click interface.
Customers now have a clearer path to augment client and server-based analytics tool sets with a solution that is specifically built for Big Data solutions like Apache Spark. “Efficient model building and easy-to-understand visuals that Decision Trees bring to data science teams allows users to not only create analytic models to generate insights and predictions, but they can also manipulate, combine and profile data sources entirely within a Spark cluster,” said Rami Chahine, Vice President, Product Management. “All while delivering the same workflow building experience that customers have come to value, with intuitive, interactive workflows and no need for coding.”
Data science teams that are modeling in a Big Data environment, and outside of it, can use Angoss KnowledgeSTUDIO for Apache Spark to efficiently build analytic workflows using large, small and wide datasets in a Spark environment. Datawatch Angoss market-leading decision tree interface can now be used by data scientists and business analysts, without having to move data out of Spark.
As with other Datawatch solutions, Angoss KnowledgeSTUDIO for Apache Spark requires no coding expertise. Users working to address business problems can now support advanced modeling with open source packages such as SparkML, Spark SQL and file systems accessible via Spark interfaces. Data preparation and profiling allow for easy data extraction and manipulation, and data can easily be transformed for modeling.
“Angoss KnowledgeSTUDIO for Apache Spark allows business users to create predictive models at scale, from a variety of datasets regardless of their size,” continued Chahine. “This more efficient use of compute resources, especially in cloud environments, shortens processing cycles and can reduce costs.”