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In an IoT / internet and things based system or data-oriented enterprise application, a myriad of data is generated on a daily basis in the form of logs, readings from the sensors, users’ comments and reviews, etc. This data contains insights that can be of great business value. But before realizing any real value, the most significant challenge is to find the optimum way to warehouse and then mine this data for business-driven decision making.
This white paper describes two simple but popular data mining techniques—linear regression (in R) and Spring Batch—by working through a use case in the form of an app called Electrack, which helps users minimize their electricity expenses by keeping track of their daily consumption.
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