The IoT is that technology that is influencing eveiy domain possible from daily life, to business to even the economy as a whole. Since the world is making advances at a very rapid rate, BA are bound to increase and IoT has allowed making an impactful connection between people and things at any tune or place with the help of individual networking devices. It is merely making devices talk to each other on a simple and easy note. These include everything ranging from smart systems to wearables, mobile phones, healthcare equipment, security devices to smart homes and smart cities.

Many events and procedures are still in progress and many have become realities to redefine IoT concerning BA and world-changing business models. This also helps in establishing a network between endpoint



Key Elements




Object Automation Model

Software, Information. Customer Report

Physical objects were digitized using the various technologies to establish digitalized gain characteristics.

Yoo et al., 2010


Business Canvas Model

Subscription Fees, Usage Fee, Software, Information. Customer Resource

A value proposition and customer perspective based business model by taking the importance of information into consideration

Bucherer and Uckehnann. 2011


DNA Model

Software, Information. Customer Resource. IT Cost, Infrastructure, Software, Information. Customer Resource

A business model based on Design. Needs, and Aspirations. This model is used to build a strategic approach towards business and management.

Sun et al., 2012


Multiple open platform (MOP) model M2M model

Performance, Customization. Share. Convenience IT Cost, Infrastructure

A multidimensional structure consisting of var ious dimensions such as technology, industry, policy, and strategy The macliine-to-macliine connections increased drastically and reached 195 million

Li and Xu. 2013


Business canvas model

IT cost, infrastructure, convenience, customization. Integration Ability, Software Developer. Data Analyst

Looking at Business models with the block perspective. Every model was now thought of as a mixture of several building blocks compiled together

Dijkman et al., 2015


Stage-Gate system model

New innovation approaches, software, information

An IoT based business model aiming at shortening technological cycles, thus creating new innovation approaches.

Tesch et al., 2017


Sendee Business model

Manufacturing firms, software. Customer Resource. Management. Platform & Resource Integration Ability

This is a six parameter guiding business model for manufacturing firms based on the application of IoT offering new opportunities of design, technical, and ecosystem lens

Lai et al., 2018

devices for system reliability and focused management (Leminen et al., 2012; Xiaocong and Jidong, 2010).

The concept of IoT in Business dates back to 1999 when British entrepreneur Kevin Ashton used it to name the communication system of the material world with computers by using sensors in which objects had direct or indirect data collection, processing or exchange attributes (Ashton, 2009). The BA foundation saw a significant rise in 2008 and 2009 when the number of devices comiected on the internet exceeded 6 billion. CISCO Systems Inc. called it the Internet of Everything. So, this was how IoT came into the business scenario. The introduction of IoT in the business sector as an attribute has its pros and cons. On the one hand, it acts as a tool for connecting people, connecting devices, making them smart for technological and economic growth with the proper transmission and handling of data over the internet, but on the other hand, there exist technological pull forces where existing areas are analyzed for the benefits by the widespread deployment of IoT.

A graph representing the number of installed devices in the recent years and number of expected installed devices in the upcoming years is shown in Figure 10.1.

Graph showing the number of installed IoT devices (year wise)

FIGURE 10.1 Graph showing the number of installed IoT devices (year wise).

IoT has facilitated global networking by connecting a vast and varied amount of devices, people, and goods all over the world, thus grasping both the providers’ and the users’ attention in a single framework (Yeipude and Singhal, 2017).


Specifically, BD is the coimecting link between IoT and BA. The use of BD arises due to the need for management, transmission, operation, storage, analysis, and visualization of a large amount of data over the Internet. It is a reflection of the changing world we live in. The more things change, the more the data is generated and recorded for future use. So, here it works on a simple mechanism. Each body is given a unique and different accessory to collect data as much as possible without any ambiguity using a network. All this data collection can be further processed to reach useful results, hence marking the exciting trends based on advanced analytics models. This process of churning and management of massive data implementing avant-garde analytics technique to dredge-up hidden patterns and correlations is termed as BA (Sagiroglu and Sinanc, 2013). FACTORS

The three main deciding factors of BD are 3Vs:

  • • Variety;
  • • Velocity; and
  • • Volume.

Variety means a wide variety of data are supported which can be even interchanged into the required format. It also refers to the enormous variety of ordered and disordered data such as texts, tweets, pictures, emails, and many more. By velocity, it means it’s capability of handling all types of data whether the sensor data or stock data or large volumes of data. The same is shown with the help of Figure 10.2.

Data is growing at a million rates causing nuclear data explosion. BD comes to the rescue of enterprises against this nuclear data explosion, making incoming of data faster and reducing processing time to prevent blockages. Volume refers to the management and processing of a massive amount of data. It encompasses the data available to be assessed for relevance. There are millions of people sharing data and with increased amounts of IoT devices, data generation is on a high rate, resulting in the large amount to volume in BD analytics.

The 3 Vs of big data

FIGURE 10.2 The 3 Vs of big data.


A click away from self-service-BD has made it possible for companies to expand their services and products with just a click of a button without involving any human intervention:

  • 1. Resource Pooling: Using a multi-tenant model, resources like storage, memory, virtual machines (VMs) can be grouped for efficient usage.
  • 2. Availability of Data: Information is available all time over the network and can be accessed with various devices simultaneously.
  • 3. Elasticity: Resource elasticity means resources can be increased or decreased as per customer’s need.

The use of BD is expanding at a rapid rate in all domains of life including engineering, biological, and biomedical domains. In the purview of the growth in the number of connected devices using IoT, this led to an increased amount of data to manage, that completely reflects how and why BD overlaps with that of IoT. The concept of BD completely nullified the need for transactional data produced manually. Instead, BD with the IoT networks unfolding all over the world gave rise to a new feature of sensor data in which data is generated and collected by the connected IoT devices (Barnett, 2015).


BA mainly refers to technologies, applications, and practices for the collection, processing, and analysis of data to yield fruitful outcomes and working with these outcomes to ensure better customer results (Balachan- dran and Prasad, 2017). The primary purpose of BA is to ensure fast and reliable decision making. This is highly required in any business domain to be successful and to land on marks amidst the competing world outside.

No set of humans can collect, store, and analyze such a vast amount of data present today in the world; then there comes the role of BD that helps business models to deal with an enormous amount of structured, semi-structured, and unstructured data. This evolving and meaningful data analyses, data sets to uncover unknown patterns and insights. The comprehensive goal of BA is to extract useful information from all data available to transform into a coherent structure for further use. The processing of data implementing the advanced techniques in the Business domain to derive and predict useful decisions is called BA (Yerpude and Singhal, 2017).

BA has been further divided into descriptive, predictive, and prescriptive analytics as shown in Figure 10.3. A closer look shows that:

  • 1. Descriptive Analytics (DESCBA): This uses data mining, intelligence, and web analytics to present the trending infonnation of the near past and current events, helping business models to know what are the demands and drawbacks of the market.
  • 2. Predictive Analytics (PREDBA): This uses statistics and network analytics to forecast future models.
  • 3. Prescriptive Analytics (PRESBA): This uses AI, optimization, and reasoning to provide the most suitable set of models for the organization to choose from indicating the pros and cons of each.

These layers also contain two interconnected analytics: Inquisitive Analytics and Preemptive Analytics. The inquisitive analytics uses statistical and factor analysis to approve/reject business prepositions while the preemptive analytics concerns with the precautionary actions on adverse events, providing alternative and sanative strategies to cope up.

Different types of business application analytics

FIGURE 10.3 Different types of business application analytics.

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