Analyzing the Internet of Things Data

Companies are jumping on the Internet of Things (IoT) bandwagon and for good reasons. McKinsey Global Institute reports that the IoT business will deliver $6.2 trillion of revenue by 2025.

What makes IoT possible, besides ubiquitous embedded sensors, is the sensors’ ability to transmit digestible data in real-time and Hadoop 2 clusters’ capacity to absorb and process voluminous data at petabyte scale. At the heart of the processing voluminous sensor data at scale are three major steps:

  1. Data Ingestion or harvesting  (Apache Kafka and Apache Storm)
  2. Data Storage (Apache Hadoop Distributed File System)
  3. Data Analytics (Apache Hive, R programming language)

The value of IoT is in the data. The quicker enterprises can start analyzing their data the more business value they can derive. Vendors are stepping up to the plate to remove the complexity and risks of data ingestion and data management so that customers can focus on analytics.

Revolution R Enterprise is a production grade analytics software product built by combining the powerful open source R statistics language with commercial enhancements and professional support necessary for enterprise deployment.

Revolution R Enterprise powers Big Data analytics with a series of unique innovations:

  • Freedom From Memory Constraints enablesanalysis of terabyte-sized data sets
  • Transparent Distribution of Computations distributes work in parallel to all nodes of clustered systems to maximize computational scale
  • Runs Analytics In-Database and In-Hadoop runs sub-tasks on nodes closest to the data, eliminating data movement and maximizing throughput
  • Accelerated R Interpreter speeds through analytics using linear mathematics libraries optimized for multi-threaded, multi-core and distributed execution

 

R: The most powerful and most widely used statistical software

 

Achieving High-Performing, Simulation-Based Operational Risk Measurement with R
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