SAS® Analytics for IoT

Access, organize, select and transform IoT data with this complete, AI-embedded solution. SAS Analytics for IoT covers the entire Internet of Things analytics life cycle, providing streamlined, extensible ETL, a sensor-focused data model, advanced analytics, and an industry-leading streaming execution engine to perform multi-phase analytics. SAS Analytics for IoT is built on SAS® Viya® and runs in a fast, in-memory distributed environment.

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The most recent release is SAS Analytics for IoT 7.1.

What’s New

Automated ETL tasks

  • Rapidly load IoT data, whether you have three fields (sensor ID, value and date time) or hundreds.
  • Include sensor attributes, device attributes, hierarchies, measures and events.
  • Integrate additional field and production quality data with your sensor data, using comprehensive ETL capabilities.

Flexible data model for sensor data and related domains

  • An out-of-the-box way to store complex IoT data, hierarchies and other relationships.
  • A proven way to organize large volumes of diverse IoT data for efficient analysis.
  • A single version of the data for a diverse array of users across the organization.

Integrated, business-focused data selection user interface

  • Access available variables and attributes in their own business terminology.
  • Use smart filters, predefined date windows and other shortcuts to increase efficiency and reduce errors.
  • Select data for any combination of devices, sensors, measures and events to support their individual needs.
  • Save, copy, reuse and share data selections across the organization.

Launchers that make data preparation and transformation easy

  • Transpose data from an efficient storage format to an analytics-ready format.
  • Interpolate missing values in the data.
  • Apply a fixed periodicity to reduce data size or commonize across sensors.
  • Open the data in SAS Visual Analytics, SAS Visual Data Mining and Machine Learning, and SAS® Studio, as well as third-party and open source applications.

Advanced analytics and machine learning in a unified, scalable environment

  • Analyze data without writing code, using a drag-and-drop interactive interface.
  • Rely on best practice templates (basic, intermediate or advanced) to get started quickly with machine learning tasks.
  • Apply diverse machine learning algorithms – including decision trees, random forests, gradient boosting, neural networks, support vector machines and factorization machines.
  • Compare results of multiple machine learning algorithms with standardized tests to automatically identify champion models.

Public APIs

  • Integrate SAS or third-party solutions into your IoT ecosystem.
  • Automatically populate external dashboards and reports with the latest data or lists of data selections.

Documentation

Find user's guides and other technical documentation for SAS Analytics for IoT.



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SAS Analytics for IoT Blogs & Communities

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