With Volery IoT Analytics solutions we enable your organization to execute and automate data analytics to leverage your IoT Data, which is a very challenging task if one looks at the mass of data to be processed. Generating insights is essential to gain hard facts and to make the right decisions at the right time.
In general, IoT-Data have a complex nature, are often not reliable, only make sense with additional data from external sources, and usually occur in huge volumes. This makes it impossible to derive satisfying results using conventional data analytics methods and tools. Volery IoT Analytics solutions provide flexible tools and methods to (a) enrich your IoT-Data with external data sources (b) transform your IoT-Data into an analyzable format (c) realize your analytical tasks e.g., making predictions, use machine learning models, and (d) deploy and report the results to an easy-to-use application.
Volery IoT Analytics solutions enables you to use the most suitable algorithms for your analytical tasks e.g., the forecasting of future sales trends or the clustering of Wireless Sensor Networks to optimize its efficiency, as well as the most efficient toolset to report results in an appropriate manner.
The choice of the right machine learning library depends on multiple factors such as the underlying data to train and test the model, the use-case and characteristics of the analytical target, the application and analytical needs, as well as the level of comfort and previous experiences. Common ML libraries that harmonize well with Volery and our IoT Analytics services include, Tensorflow[.js], Keras, PyTorch, R, and Java-ML just to mention a few of them.
Reporting results to a decision maker or a data analyst in an appropriate manner is one of the most important steps in an Analytics Pipeline. Our IoT Analytics services are able to utilize Analytics-Platforms (e.g., Tableau, PowerBI, Qlik, and many more) to report results and monitor important processes.