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. Learn how to build SAS Event Stream Processing applications that ingest high-volume and high-velocity data streams, respond in real time, and store only relevant data elements. This course covers basic concepts of event stream processing, including what component objects are available to build event stream processing applications. Curiosity is our code. SAS analytics solutions transform data into intelligence, inspiring customers around the world to make bold new discoveries that drive progress.
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SkkyHub
For most IoT services, the cloud is an end point. With SkkyHub™, the cloud becomes a way to stream your data from wherever you have it to wherever you need it. Connect OT to IT, do M2M, or link remote locations, all streaming in real time—just microseconds over network latencies. Stream data from your devices or plants for monitoring, or stream commands, updates and configuration back to your system, or both. The DataHub gateway and ETK-enabled endpoints use the DHTP protocol to ensure a data-only connection. No VPNs means that your OT and IT networks remain untouched. Outbound connections via DHTP keep all in-bound firewall ports closed. There are no exposed attack surfaces at your facility, device, or office. Get the full picture by streaming up to 100,000 data points in real time. Three service types, Basic, Standard, and Professional, let you choose the level of service you want at a price that fits your budget.
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GroveStreams
Whatever industry you work in, the GroveStreams Data Analytics Platform can provide you with the building blocks and tools you need to create solutions tailored to your customers' needs. Visit our Developers page for a list of examples. Model time-of-use block rates for multiple locations. Precisely monitor energy usage across thousands of meters/sub-meters for apartment-level energy billing. Alert when energy usage exceeds predetermined levels and take action to reduce energy usage. Monitor water flow in remote or hard to access locations (apartments) to check for costly leakages or excess flow. Monitor propane tank levels for rural and route shipments accordingly. The Grove Streams Data Analytics Platform is a cutting-edge cloud-based service providing decision making capabilities to many users and devices as data arrives from many sources.
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Apache Storm
Apache Storm is a free and open source distributed realtime computation system. Apache Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Apache Storm is simple, can be used with any programming language, and is a lot of fun to use! Apache Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Apache Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate. Apache Storm integrates with the queueing and database technologies you already use. An Apache Storm topology consumes streams of data and processes those streams in arbitrarily complex ways, repartitioning the streams between each stage of the computation however needed. Read more in the tutorial.
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