IOT data analysis at scale with Tableau and SNAP

SNAP, is being used by ad-tech, fortune 50 and in general, companies that have large amounts of data. An area that SNAP is particularly good at is analyzing multi-dimensional data for very fast ad-hoc queries. Structured IOT data and machine data from sensors in devices are particularly suited for this.

For example take a sample dataset recording readings from sensors every minute about temperature and humidity as well as 10 different sensor readings of a machine’s various metrics.

Tableau can be used to map and analyze sensor readings and the sensitivity of the readings to external temperature and humidity even at terabyte scale, directly against live data, with SNAP.

SNAP’s in-memory cubes are exposed to Tableau for interactive analysis.

The advantage of using SNAP is that you can connect Tableau to the live dataset and eliminate extracts.  There is no need to build materialized cubes on Hadoop. SNAP works with Spark directly on your data in HDFS or S3.

SNAP’s ultrafast response comes from its optimization engine coupled with an in-memory OLAP index.

Contact us for a customized demo on your IOT dataset powered by SNAP with Tableau.


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