Sentenai Sensor Data Cloud Debuts
November 21, 2017
going beyond the initial harnessing of
machine-based data and understanding the
information that data provides,
organizations can streamline their
operational processes and develop predictive
maintenance solutions that decrease
unplanned downtime. With its Sensor Data
Cloud, Sentenai is empowering businesses and
their data scientists to build on
sensor-based applications by allowing them
to access historical data in the tools they
already use, without requiring any data
•Secure and scalable storage of sensor data. The cloud service provides a fast, flexible way to store a multitude of streams of sensor data for later data science and machine learning use, and its sensor-focused time series database preserves original data without sacrificing scalability, reliability or query performance.
•On-demand ETL pipeline for data science. By providing a powerful query engine that allows data scientists to perform ETL on-demand -- without writing code or waiting hours for results -- the Sensor Data Cloud simplifies the process of data preparation, automatically filtering noise from streams of sensor data, reshaping complex data to fit specific machine learning models, filling in missing data and normalizing data for sensor fusion.
workflow integration. Designed specifically
for data scientists, the Sentenai Sensor
Data Cloud can be implemented within
existing workflows, including sophisticated
open source data science toolkits such as
Pandas, Tensor Flow, pyTorch, and scikit-learn.