What sensor data analytics is and its use in organisations

Sensor data analytics is the future of businesses and organisations globally.

Sensor data analytics is going to play an integral role in an organisation’s success. Whether it is mining, green technology or software development, the future of all industries will be highly dependent on sensors – devices that can collect information to be stored in data lakes and fed into data analytics programs for further processing. With IoT set to make a huge splash (experts estimate that there will be over 20.8 billion IoT devices by 2020), which is why now is the time to discuss the analytics programs built to analyse data coming from these devices.

What is sensor data analytics?

Sensor data analytics is an analytics platform built to analyse the data streamed or collected from sensors and IoT devices. The data is analysed to give insight into the current status of this device using different metrics (these metrics are set based on the organisation’s needs).

There are two types of data analytics platforms, the first is ad-hoc sensor data analytics, the second is real-time sensor analytics. Ad-hoc data analytics allows data analysts to collect and analyse data, but only at specific time intervals. Meanwhile, real-time data analytics allows analysts to assess data, as it is streamed from the device in real-time.

How does sensor data analytics operate in the wider architecture?

Before diving into how sensor data analytics works in different industries, it is important to get a sense of how it operates.

Sensor data analytics works via an architecture with the sensor acting as the starting point, it collects data and transfers it to a data lake, a reservoir that stores data in its natural format. If data needs to be cleaned, groomed and dressed for analysis, then it is transferred to a data warehouse.

Along with the data lake, the data warehouse will draw data from control applications and machinery configurations to get the whole picture of the architecture. Hence, the data warehouse knows not just the type of data sensors collect but also where these sensors are placed, in the context of the overall system architecture and the variables they are measuring.

How is it implemented in different industries?

Sensor data analytics helps organisations perform two vital functions: draw tangible, relevant connections between huge data sets from different sources and formats and gain meaningful insights on traditional systems.

Faster anomaly detection

Thanks to sensor analytics, organisations can detect machine and device failures as soon as they happen, and takes pre-emptive maintenance measures to make sure the devices are functioning at full capacity. With data analytics, organisations can save thousands, if not millions of dollars because it prevents a disaster due to fast, efficient and responsive anomaly detection.

Predictive maintenance

We have discussed the value of predictive maintenance and how it can be a huge cost-cutter for organisations, especially in industries that are capital intensive. Sensor data analytics can measure different attributes related to wear and tear, as well as predict when maintenance is needed before the machine breaks down or if there is a notable drop in productivity. Thanks, to analytics, organisations can transform their production chain by pre-empting maintenance to make sure their supply chain operates at optimum capacity.

Analyse IoT devices for consumer data

IoT provides a rich source of data on consumer behaviour, given that organisations can now use the information to execute strategies that are sure to improve customer relations and strengthen brand loyalty. This includes user behaviour, segmented marketing, personalised customer interactions and tracking product usage. However, to take advantage of this data, organisations need sensor data analytics to work. Without analytics, it would be very difficult to analyse data, as it is streamed.

Investing in the future with analytics

IoT devices are going to play an even bigger role in our lives in the near future, so sensor analytics can be seen as an investment for the future. Furthermore, organisations are looking to operate smarter and be more efficient, as a means of cost-cutting and increasing profits. Considering all these factors, it becomes important to invest in an analytics platform that can stream and analyse data in real-time from different devices, which is why sensor data analytics is so important to business operations.

Sensor data analytics can, and will, help transform the way businesses operate by reducing costs, working smarter and, consequently, increasing profits.

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