How IoT Analytics Can Help Your Business to Achieve Success

Jan 2nd, 2023

How IoT Analytics Can Help Your Business to Achieve Success

Globally, IoT (Internet of Things) has marked its presence with the definition – “A network of connected devices or other physical entities ,i.e., “Things” that gather information with the help of smart chips, sensors, gateways and transfer it to other endpoints that can be accessed by humans.” This buzz-created word “IoT” proves itself a powerful technology in the procedure of digital transformation of any business, including manufacturing, retail, healthcare, logistics, and many others. 

But, now to offer more value to businesses, IoT requires to add some capabilities through its integration with Data Analytics. This emphasizes IoT Application Development Services providers to work more toward creating a stronger foundation for businesses with the development of right IoT analytics solutions.

Overview of IoT Analytics 

Collecting and storing information is not enough for any business to drive values like enhanced bottom line, improved productivity, and efficiency. From the vast pool of produced data, fetching meaningful insight has seized the attention of industries. Here, Internet of Things Analytics comes into the frame. This combination of IoT and Data Analytics benefits business encircling apart from just consuming data.

IoT Analytics holds separate power and potential that emphasizes industries to embrace it and get a kick out of this technology. Enhanced efficiency, productivity, predicted maintenance, and improved customer experience are some key benefits that come with the wave of IoT Analytics.

Before concluding about the integration of IoT Analytics Platform in business operations, let’s discuss what exactly IoT Analytics is.

IoT App Solutions- Benefits, Challenges

What is IoT Analytics?

Simply put, IoT Analytics consists of the process of performing several activities, such as analyzing, and filtering the data that has been collected through IoT-connected devices, sensors, and other things to produce intelligent data or actionable insight.

IoT devices collect and store a vast pool of real-time unstructured data on various ongoing business operations. Data is collected from the range of sensors, which are useless until it can be converted into something worth data. Here, to address this challenge, businesses can adopt IoT Analytics to manage data from its production to analysis.

IoT analytics involves applying data science techniques to the massive amounts of data collected by IoT devices in order to derive actionable insights. Predictive maintenance, supply chain management, and prescriptive analytics are common uses for IoT analytics.

Why Does IoT Analytics Matters for Businesses?

As per Statista research, approximately 14 billion devices connected to the internet in 2022 which is going to reach 26.29 billion by 2030. On a daily basis, these IoT devices produce enormous amounts of data, the biggest and noteworthy challenge encountered by people, businesses, and organizations is to bring out relevant and useful data for further business sustainability.

IoT Analytics Statista

The volume of generated data through IoT devices is increasing unstoppably. This research is evidence of how dramatically data production amplifies in the wink of an eye. Also, a predicate that figure will definitely boom in the future. As per the Statista, By 2025, total data volume of connected IoT devices worldwide is forecast to reach 79.4 zettabytes (ZBs).

For the success of IoT, data analytics is essential. The IoT requires the integration of all of these sorts of analytics, including streaming data, to evaluate and filter the fast-moving data. Analytics are often used for reporting, diagnosis, prediction, and other examples of advanced analytics.

IoT data Analytics has capabilities to fill the existing gaps experienced by an entrepreneur in business models, processes, and operations and unleash new opportunities for business growth. Moreover, its ability to successfully transform raw data into usable information and insight by processing huge amounts of data to find patterns and make predictions open the door for businesses to create data-driven functions. 

Now it has become possible for businesses to find patterns in data sets, including both present conditions and historical data, which can be used to forecast and modify upcoming events. Ultimately, with the embracement of IoT Analytics, all sizes of organizations can move forward with confidence and set the high bar for competition. 

Here is a quick example:

The program or application that links your smartphone to your thermostat can perform data analysis under the IoT analytics. It will then translate that information into an understandable chart, often a bar graph that displays your consumption by week, month, and year.

What makes IOT Analytics Different

Businesses can leverage IoT Analytics for multiple reasons, following are the mentioned below:

  • To enhance data driven decision making process
  • To bring business sustainability and growth
  • To reduce operational cost 
  • To enable smart utilization of asset, equipment  and other resources
  • To get instant solution of any occurrence challenges 
  • To preventing recurring problems and challenges
  • To streamline product deployment

Overview on Keywords Associated with IoT Analytics

Overview on Keywords Associated with IoT Analytics

1 . Big data: 

In the context of IoT analytics, big data plays a critical role in extracting valuable insights and making informed decisions. By analyzing and interpreting this data, organizations can gain a better understanding of their operations, identify trends and patterns, and optimize processes and systems.

2. Machine learning: 

Machine learning algorithms can be used to analyze and interpret the data generated by IoT devices, allowing for more accurate and efficient analysis. As machine learning is the part of Artificial Intelligence, it can be trained to identify unusual patterns or deviations in the data generated by IoT devices, which can be used to detect potential problems or failure. This process enables businesses to optimize processes or systems based on these insights.

3. Predictive analytics: 

Predictive analytics involves using historical data and machine learning algorithms to predict future outcomes or trends. This can be useful in the context of IoT analytics for predicting maintenance needs or identifying potential problems before they occur.  This can help to prevent costly downtime and improve efficiency.

4. Cloud computing: 

Cloud-based systems are often used to store and process the data generated by IoT devices, as they offer scalability and flexibility. With cloud computing, you can store and analyze a large amount of IoT data along with the ability to process it. Cloud based IoT Analytics satisfied the requirement of businesses’ storage space for IoT sensors to generate data.

5. Data visualization

Data visualization tools, such as charts and graphs, can be used to clearly and effectively communicate the insights and findings generated by IoT analytics. Beside, this also streamline the process of analyzing data and bring efficiency.

Concluding Lines for IoT Analytics 

The mixture of IoT and data analytics can offer businesses more than we think. Since the inception of IoT Analytics, it has traveled far from people’s expectations and turned into an integral part of processes. If you are looking to transform your business and be ready for the future market, then you highly require IoT Analytics integration into your business. It will empower you to emerge as a data-driven organization.

Solution Analysts, is here – IoT Application Development Services Provider. We have a vast knowledge of market trends and modern business requirements. Moreover, our professional team of IoT is capable of addressing any business challenges by providing top-notch & innovative solution solutions. Drop us a quick mail at [].

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