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The Growing Role of Data analytics in the Internet of Things (IoT)

Introduction

By LekhanaPublished 2 years ago 3 min read

Introduction

Data and IoT continue to be inextricably connected. Data production and consumption are growing exponentially. Since there will be almost 30.73 billion IoT-connected devices by 2020, this data deluge encourages widespread IoT adoption. In order to accomplish a common objective, many devices, networks, technologies, and human resources are connected through the Internet of Things (IoT). Numerous IoT-based apps are in use across multiple industries and have been enormously beneficial to their customers.

Data analytics come into play since analyzing the IoT device data makes it valuable in the first place. Data analytics (DA) is a procedure used to analyze large and small data sets with various data attributes to draw meaningful conclusions and helpful information. These findings, typically presented as trends, patterns, and statistics, support corporate organizations in actively utilizing data to implement efficient decision-making procedures which can be mastered with the IBM-accredited data analytics course in Bangalore.

IoT and Data Analytics Integration Will Benefit Businesses

The expansion and achievement of IoT applications and investments depend heavily on data analytics. The business units will be able to utilize their datasets effectively by using analytics tools, as described in the following points.

Volume

IoT applications utilize massive clusters of data sets. Business firms must manage these vast amounts of data and analyze it to find pertinent patterns. Data analytics software makes evaluating these datasets and real-time data simple and effective.

Structure

Data sets in the Internet of Things applications might be unstructured, semi-structured, or organized. The data formats and kinds could also differ significantly. The corporate executive will be able to use automated tools and software to analyze all of these various data sources thanks to data analytics.

Driving Revenue

The business units will be able to learn more about the preferences and choices of their customers thanks to the use of data analytics in IoT initiatives. As a result, services and offers would develop to meet the needs and expectations of the clientele. The organizations' revenues and earnings will consequently increase as a result of this.

Competitive Edge

IoT is a popular term in the modern technological era, and many IoT application providers and developers are on the market. A business unit will be able to offer better services and, as a result, obtain a competitive edge in the market by utilizing data analytics in IoT investments.

In order to benefit from IoT investments, various forms of data analytics can be leveraged and applied. The list and descriptions of a few of these types are provided below.

Streaming Analytics

This type of data analytics, also known as event stream processing, examines enormous quantities of in-motion data. This method evaluates real-time data streams to find urgent problems and take prompt action. This technique can be used for Internet of Things applications based on financial transactions, air fleet tracking, traffic analysis, etc.

Spatial Analytics

In order to ascertain the spatial relationship between the actual items, this data analytics technique analyzes geographic patterns. This kind of data analytics can be helpful for location-based IoT applications, including smart parking apps.

Time Series Analytics

As the name implies, this type of data analytics is based on time-based data that is examined to identify related trends and patterns. This type of data analytics technique can be helpful for Internet of Things applications like weather forecasting software and health monitoring devices.

Prescriptive Analysis

This sort of data analytics combines descriptive and predictive analysis. It determines the optimum course of action that can be followed in a specific circumstance. Commercial IoT applications can use this type of data analytics to draw more accurate conclusions.

There have been instances where data analytics applications and usage have greatly benefited IoT investments. There are new fields where data analytics can be used in conjunction with IoT due to changes and advancements in technology. For instance, actionable marketing can be done by using data analytics to analyze how customers use the product. Through the use of video sensors and data analytics techniques, IoT analytics will also enable greater security and surveillance capabilities.

Every country's top industry is healthcare, and using data analytics in IoT-based healthcare applications can lead to advances in this field. It is possible to reduce healthcare expenses, improve telehealth monitoring and distant health services, and increase diagnosis and treatment by using the same.

Conclusion

Therefore, data analytics and data science must be encouraged in the IoT space to boost sales, gain an advantage over competitors, and increase consumer satisfaction. Businesses can combine data analytics with IoT to use data to their advantage by working with the right strategic partner. To gain an in-depth knowledge of data science in IoT, join the data science course in Bangalore and implement your acquired knowledge in various domain data science projects.

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