We will touch on a few industries to discuss special consideration for IoT data exploration and analysis.
For IoT data generated during the manufacturing process, the accuracy of recorded values is especially important. Explore the data for outliers and analyze distributions carefully. Verify all the data ranges and distributions that you see with the experts on the manufacturing process.
The benefits of making sure the measurement values are clean as possible are two fold. First, any machine learning models created to detect problems will be significantly more accurate. Secondly, false positives due to invalid data can have a high penalty. The manufacturing line and product deliveries may be halted while the issue is investigated. In manufacturing, this can get expensive quickly. More perniciously, the long-term effect of false positives tends to be the complete rejection of the analytics by company management, when they no longer trust...
