Fig: IoT Analytics process flow on Data Lakehouse
The Internet of Things (IOT) is a network of physical devices. These devices are characterized by a Unique Identifier (UDI) and a sensor. They are essentially self-reporting devices that send signals (data) to each other or a centralized computer server. Home security devices, wearable computing like smart watches, personal medical devices like pace maker, industrial sensors are some examples of IOT devices. IOT Analytics is about analysing the data collected from the IOT devices.
The data transmitted by an IOT device may be a continuous or intermittent stream of measures or voice or images. The data may be real time or may be sent intermittently, depending on the connectivity and use case.
Artificial Intelligence can be of immense support in processing IOT data. Here we list some common techniques used:
As evident from the discussion so far, IOT analytics is at the intersection of several disciplines. It requires expertise in Big Data processing, Streaming data processing, Data integration, Data quality, Security, Data Wrangling, Data Analysis, Cloud Data Warehouse, dashboards, Machine Learning, Natural Language Processing, predictive modeling, prescriptive modeling and pre-emptive modeling.
Y Point analytics has expertise in all these inter-disciplinary skills and also has proven experience in rolling out high quality solutions as per plan backed by its time tested project management and delivery practices.