The development of Internet of things (IoT) is rapidly accelerating and affecting the industries directly or indirectly. This is steadily increasing the data generated by the business specific IOT-devices around the globe leading to one of the major challenges of the IOT industry that is collection, processing, analyzation and visualization of the data collected from different sensors in the IoT environment. Thus, with an exponentially growing volume of data, the need to interpret and make useful insights from the data is making Data Visualization an integral part of IoT.
Role of Data Visualization in IOT
Data Visualization
Data Visualization is referred as the process of representing information or data into a visual context that provides useful insights from the data. It is a way to display the vast amount of data in a meaningful way that clearly presents trends and patterns from the raw data collected.
Data Visualization tools and technologies help to slice and dice the data to the minute granular level.
Need for data visualization
The real purpose of Data Visualization is nothing but ‘making sense of data’. It provides a quick and effective way to communicate information to identify trends and patterns and flag inconsistencies and errors in the data. It gives enterprises the ability to rapidly and effortlessly make decisions, visualize the output to monitor results, get actionable insights and evaluate the factors affecting businesses and customer behaviour.
A good visualization tells a story, removing the noise from the data and highlighting the useful information.
Role of data visualization in IOT
Internet of Things (IOT) and data are interlinked together as IOT is all about collecting data and making sense of it. One of the challenges for IoT industry is data analysis and interpretation. Trillions of data is generated every day from the IOT sensors and devices in the physical world and this data can potentially become a source of business value. The data collected is impractical if we cannot extract useful information from it and analyse and translate that information to identify hidden trends, outliers, and patterns in data and make data-driven decisions.
The continuous acquisition, storage, analysis and implementation of data from IOT devices can help companies identify bottlenecks in supply chain, predict equipment failure, successfully address overstaffing issues and optimize operational costs therefore improvising business productivity and outcome.
The objects in the physical world are connected and enhanced with temperature, moisture, light, motion, location and other types of sensors which produce the real-time timeseries data and send this data to the cloud where it is stored for analysis and interpretations for making smart decisions. Considering an example of data collected from the sensors connected to the windmill of a windfarm, sensors are connected to various components of the windmill to calculate the wind speed, energy produced and temperature of different components of the windmill. The representation of data in visual context rather than being in textual format gives the ability to absorb information quickly, improve insights and make faster decisions.
Data visualization provides an opportunity to see patterns that may remain hidden in those datasets if not analysed properly and can assist in making fast, informed decisions with more certainty and accuracy. The insights and relevant correlations represented from the visual representation can allow companies to solve business problems, drive sales, cut costs, find new revenue streams and take smarter decisions.