IoT Analytics: Challenges, Benefits and Must-have Features

Last Updated on December 7, 2022

The internet of things is becoming a reality. With the increasing prevalence of technology in our daily lives, the idea of an internet-connected world has taken form. Recently advanced sensors and embedded devices are transforming our world into a data-driven infrastructure. To capitalize on the countless opportunities offered by this new technology, it is essential to invest in the help of analytics to provide actionable insights.

IoT analytics solutions are becoming a necessity for companies. They need to make sense of the data generated by these products to make informed decisions. To do this, businesses must adopt analytics platforms covering all aspects of the connected world. Here we will discuss IoT analytics and some benefits and challenges of implementing these solutions.

What is IoT Analytics

IOT Analytics
Source: IoT-analytics

IoT analytics refers to data analytics performed over the internet of things. Data is continuously generated from connected devices. Sensors and embedded processors collect data from the device and store them as raw signals. The data is forwarded to an analytics server, where it is processed.

There are varying methodologies used to process and analyze the data. Correlation analysis will identify latent relationships between variables. Time-series analysis looks at the value of different variables over time. Market basket analysis can identify potential new customers in a business. The data can be leveraged in different ways depending on the purpose of the analytics.

Challenges of IoT Analytics

There are several challenges that organizations need to think about before embarking on an IoT analytics project. The data collected from various devices and sensors is not always in a consistent format. Some data is structured, and other data is unstructured. Some data can be easily manipulated using simple formulas, while other data never finds its way into spreadsheets or databases. The massive volume of data generated by IoT technology poses another challenge. The data needs to be stored and processed in a structured manner. Companies will have to invest in hardware that can handle the load. Small businesses face additional challenges. Due to their limited resources, they often need help with data integration and analysis. Their analytical solutions are usually limited to data from internal databases.

Implementation is also another vital concern. Connected devices are different and come with their challenges in terms of implementation. Some devices use standard protocols, while others may require custom protocols to communicate with each other and other components of an IoT network system. There may be challenges integrating these different devices onto a single platform for processing. Security issues also need to be considered carefully. Hackers and cybercriminals can hack into the technology and access sensitive data. The analytics platforms need to be robust and secure. They need reliable security features to ensure that data is always protected.

Benefits of IoT Analytics

The massive amounts of data help businesses make better decisions with a higher probability of making a positive impact. This includes pricing and promotions decisions, new product launches, and policy changes. By analyzing data in real-time, businesses can identify the right market segments at the right time. They can design the right products and services for different customer segments. They could use this data to increase margins, reduce operating costs and make profits.

IoT predictive analytics can help organizations mitigate risks associated with future events. They can scan the data to predict future happenings. This will help them make informed decisions about investments in training or preventive measures. An IoT analytics solution can also help an organization in marketing, brand awareness, and customer service. Small businesses can use the analytics platform to optimize and improve customer service for new and existing customers. This will eventually lead to increased customer loyalty, brand value, and stake in the market. IoT analytics can also help prevent fraud and theft.

How Does IoT Analytics Work

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Source: Gartner

Data analytics for IoT can be broken down into capturing, storage, and processing. Capturing refers to the gathering of raw sensory data. Sensors such as cameras, microphones, and sonar capture actual data from the surrounding environment. The data is then stored in a database. The storage process varies depending on the data type. Structured data, such as sales figures, can easily be stored in a database without hassle. Unstructured data, like video footage, must be processed using more sophisticated techniques.

IoT analytics companies will use various tools to process and transform data from disparate sources. The final result is a report that gives the necessary insights to make informed business decisions. This report can be visualized as graphs and charts. These charts provide specific time frames, locations, and data points.

Features to Consider When Choosing an IoT Analytics Platform

The platform should provide broad visibility of the processed data. Updates should happen automatically without the need to log into the platform. The platform should have various features that will cater to multiple use cases, which vary from one industry to another. The analytics platform should include modules such as machine learning, predictive IoT data analysis, and deployment of apps and dashboards. It should have an easy-to-use interface.

The platform should be able to scale as the amount of data increases with time. It should have an intuitive search function to retrieve data from the database efficiently. Reliability is another critical feature to consider. The platform should be able to process large amounts of data in real time. It should also be reliable from a security standpoint and follow the latest security protocols to protect the data it stores.

IoT analytics is at a very nascent stage. Technology companies are experimenting with new approaches and systems for IoT data processing and analysis. There will be further applications for IoT analytics once the developers understand how to process data from connected devices. IoT analytics will have a huge impact on how businesses are run and how they generate revenue. It can also help create safer cities and communities with fewer accidents and better natural disaster preparedness.

 

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