Apache Hadoop is at the core of the Big Data revolution. Vendors such as Cloudera, MapR, and Hortonworks have taken this open source software that enables distributed parallel processing of huge amounts of data, and included important data management and support capabilities.
However, many Hadoop analytic solutions are designed for a limited number of specialists within organizations, or just focus on Hadoop as a data source. Alteryx takes a different approach by humanizing Big Data, with the core goal of putting the value of Big Data in the hands of all decision makers.
Through a Hive (the SQL query layer available for Hadoop) connector, Alteryx provides a unique approach to accessing and analyzing Big Data. This connector allows data artisans to query Hadoop data using either SQL or HQL (Hive Query language), and then integrate that data with any other data source to build exactly the data set needed for analysis.
Key Alteryx capabilities for Hadoop Analytics:
- All relevant data: Access, integration, and cleaning of sources of data as varied as Hadoop (including Cloudera & MapR) or NoSQL (MongoDB) and Excel or Teradata
- Fastest Platform to build analytics: Sophisticated but accessible predictive and spatial tools, combined in a simple, workflow design environment
- Simple sharing of Big Data analytics: Single click sharing of analytic applications that can be used by any decision maker