IOT DATA VALIDATION

It is often the case that IoT systems are deployed because of a desire to monitor and collect data to get valuable insights about certain conditions and processes. These insights based on gathered data can also be used to make data-driven decisions. The benefit of IoT is that it is easy and cheap to start implementing an IoT system, maybe in the form of a proof of concept, and simply start gathering data. However, when making data-driven decisions we must take the necessary steps to consider the quality of the data collected.​ 

If the data quality is not high enough for a specific use case the data is not trustworthy and consequently if the data is not trustworthy, the insights and analytics will also not be trustworthy.

It is our experience that ensuring the quality of the data is often lacking in IoT systems. Many different errors relating to format issues, outliers, and missing data, can be found in data collected from IoT systems and they can be caused by many different factors.​ 

With IoT data validation the aim is to ensure the quality of IoT data by validating it according to certain criteria, specifications, and requirements based on the specific use case. With tools for creating a data quality declaration for setting data quality targets, and with open-source tools for analyzing and visualizing data, it is easier to determine whether collected data is fit for its intended purpose and if there is any errors, i.e. determine if data can be trusted. Based on such analysis one might also investigate why certain data errors are occurring and focus future development on mitigating those.​
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This service provides an initial review of your data. Using a stack of open-source tools, an initial data validation will be performed to find any potential errors in the data.