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Available on GSA Schedule GS-35F-0119Y Big Data Analytics For Hadoop Overview Datameer is the first and only end-user focused application for Hadoop-based analytics. It provides four key elements:
Integration Without Limits Traditional analytic solutions were never designed to handle today's data volumes, have little or no capabilities to handle unstructured data and require rigid analytic data structures such as data marts or OLAP cubes to perform well. Datameer changes all of that with the ability to integrate, transform and analyze any volume of structured and unstructured data. The resulting ability to correlate and analyze data from unstructured sources together with transaction data means that analysts and data scientists can now ask and answer analytic questions never thought possible. Datameer makes it easy to access and integrate data for analysis with:
Powerful Analysis with Extreme Scale Datameer opens big data analytics to business users through its spreadsheet-like interface that enables anyone to build powerful analytic workflows across all data types. Users can easily employ the pre-built formulas, filtering, and sorting to locate and fine-tune the specific information they need and then perform the transformations and analysis on the entire dataset via native MapReduce jobs on any Hadoop cluster of up to 4000 servers. In addition to the pre-built analytic functions provided within Datameer, analysts can apply analytic functions and algorithms from third party packages such as SAS via PMML (predictive modeling markup language) and can export results to third-party BI software applications for further analysis. Insightful Dashboards With Datameer, users can easily visualize their data via drag and drop widgets using the analytic workbooks created in Datameer. These interactive dashboard widgets allow users to access and view their data in a wide variety of graph, map, chart, table and dashboard formats.  Each dashboard widget is linked to data from an analysis workbook making it easy for business users to create their own analytic dashboards. Users simply run the workbook and then configure the dashboard widget for how they wish the data to be displayed using the extensive style library of bar, line and pie charts, tables, maps and other formats. The end result is self-service analytics and data visualization that can be easily used across the organization. Resources: |
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