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Global IoT Analytics Market to reach USD XX billion by the end of 2030

Global IoT Analytics Market Size study & Forecast, by Component (Software, Services), by Deployment (Cloud, On-Premises), by Application (Energy Management, Predictive & Asset Management, Inventory Management, Others), by Industry Vertical (Healthcare, Government & Defense, Manufacturing, Others), and Regional Analysis, 2023-2030

Product Code: ICTNGT-11143341
Publish Date: 20-10-2023
Page: 200

Global IoT Analytics Market is valued approximately USD XX billion in 2022 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2023-2030. IoT Analytics is a process of collecting, processing, and analyzing data generated by Internet of Things (IoT) devices and sensors. The Internet of Things is a network of interconnected devices, objects, and machines that can collect and exchange data over the internet without the need for human intervention. IoT Analytics plays a crucial role in leveraging the massive amounts of data generated by IoT devices, helping organizations and businesses make data-driven decisions, optimize processes, enhance user experiences, and improve overall operational efficiency. The IoT Analytics market is expanding because of factors such increasing volume of IoT data and emergence of connected cars and smart cities.

As the adoption of IoT devices continues to rise, the data generated by these devices grows exponentially, creating a massive influx of information. IoT analytics enables organizations to extract actionable insights from the massive volumes of data collected by IoT devices. These insights help businesses optimize processes, enhance productivity, reduce downtime, and make firm decisions. According to Statista in year 2019 the total data volume generated by IoT connection stood at 13.6 zetabytes and it is projected to reach at 79.4 zetabytes by year 2025. Furthermore, connected cars generate massive volumes of data from various sources, such as built-in sensors, GPS devices, cameras, and other connected devices within the vehicle. This data includes information about vehicle health, driving behavior, road conditions, and much more. The sheer volume and variety of data produced by connected cars present significant opportunities for IoT analytics. The same source projected that by year 2025, there would be over 400 million connected cars in operation across the globe which represent increased of some 237 million connected cars in year 2021. Thus, rising IoT connection data volume and rising adoption of connected cars across the world are some factors driving the growth of IoT analytics market. In addition, adoption of IoT analytics is industrial automation, increasing technological advancement and increasing IoT spending by various industries are creating new opportunities for market growth. However, concerns associated with data privacy and security stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global IoT Analytics Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to presence of key market players, rising adoption of connected devices, rising spending on adoption of IoT technologies by various end users, rising data generation and rising technological advancement in the region. Whereas, Asia Pacific is projected to grow at a significant rate owing to factors such as rising adoption of digital technologies, rising adoption of connected devices, rising investment in smart technologies in factories and industrial sectors in the region.

Major market player included in this report are:
Microsoft Corporation
Oracle Corporation
Amazon Web Services, Inc.
Cisco Systems, Inc
International Business Machine Corporation
Accenture PLC
Dell Technologies Inc
Google LLC
The Hewlett Packard Enterprise (HPE) Company

Recent Developments in the Market:
Ø In October 2022, KTD SYNNEX introduced Data-IoTSolv in the Americas, a comprehensive suite of solutions designed to empower partners in harnessing the potential of the Internet of Things (IoT) and data analytics for accelerated business expansion. With Data-IoTSolv, resellers gain access to cutting-edge technologies spanning the entire IoT edge spectrum, including artificial intelligence (AI) and advanced analytics, enabling them to deliver top-notch services to their clients. This initiative aims to drive innovation and growth by leveraging the transformative power of IoT and data analytics in the business landscape.
Ø In May 2022, Kajeet, a prominent provider of wireless connectivity, software, and hardware solutions has introduced Sentinel Insights. This new cloud-based data analytics product serves as a powerful addition to Kajeet’s flagship IoT management platform, Sentinel. By offering enhanced data analytics capabilities, Sentinel Insights empowers users to derive deeper insights and make informed decisions, bolstering the overall performance and value of Kajeet’s IoT solutions for their diverse range of clients.

Global IoT Analytics Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Component, Deployment, Application, Industry Vertical, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and Component offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:

By Deployment:

By Application:
Energy Management
Predictive & Asset Management
Inventory Management
Sales & Customer Management
Building Automation
Security and Emergency Management
Infrastructure Management
Remote Monitoring

By Industry Vertical:
Government & Defense
Energy & Utilities
IT & Telecom
Logistics & Transportation

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. IoT Analytics Market, by Region, 2020-2030 (USD Billion)
1.2.2. IoT Analytics Market, by Component, 2020-2030 (USD Billion)
1.2.3. IoT Analytics Market, by Deployment, 2020-2030 (USD Billion)
1.2.4. IoT Analytics Market, by Application, 2020-2030 (USD Billion)
1.2.5. IoT Analytics Market, by Industry Vertical, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global IoT Analytics Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global IoT Analytics Market Dynamics
3.1. IoT Analytics Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increasing volume of IoT data Emergence of connected cars and smart cities
3.1.2. Market Challenges Concerns associated with data privacy and security
3.1.3. Market Opportunities Adoption of IoT analytics is industrial automation Increasing technological advancement Increasing IoT spending by various industries verticals
Chapter 4. Global IoT Analytics Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global IoT Analytics Market, by Component
5.1. Market Snapshot
5.2. Global IoT Analytics Market by Component, Performance – Potential Analysis
5.3. Global IoT Analytics Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
5.4. IoT Analytics Market, Sub Segment Analysis
5.4.1. Solution
5.4.2. Services
Chapter 6. Global IoT Analytics Market, by Deployment
6.1. Market Snapshot
6.2. Global IoT Analytics Market by Deployment, Performance – Potential Analysis
6.3. Global IoT Analytics Market Estimates & Forecasts by Deployment 2020-2030 (USD Billion)
6.4. IoT Analytics Market, Sub Segment Analysis
6.4.1. Cloud
6.4.2. On-premise
Chapter 7. Global IoT Analytics Market, by Application
7.1. Market Snapshot
7.2. Global IoT Analytics Market by Application, Performance – Potential Analysis
7.3. Global IoT Analytics Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
7.4. IoT Analytics Market, Sub Segment Analysis
7.4.1. Energy Management
7.4.2. Predictive & Asset Management
7.4.3. Inventory Management
7.4.4. Sales & Customer Management
7.4.5. Building Automation
7.4.6. Security and Emergency Management
7.4.7. Infrastructure Management
7.4.8. Remote Monitoring
7.4.9. Others
Chapter 8. Global IoT Analytics Market, by Industry Vertical
8.1. Market Snapshot
8.2. Global IoT Analytics Market by Industry Vertical, Performance – Potential Analysis
8.3. Global IoT Analytics Market Estimates & Forecasts by Industry Vertical 2020-2030 (USD Billion)
8.4. IoT Analytics Market, Sub Segment Analysis
8.4.1. Healthcare
8.4.2. Government & Defense
8.4.3. Manufacturing
8.4.4. Energy & Utilities
8.4.5. IT & Telecom
8.4.6. Logistics & Transportation
8.4.7. Retail
8.4.8. Others
Chapter 9. Global IoT Analytics Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. IoT Analytics Market, Regional Market Snapshot
9.4. North America IoT Analytics Market
9.4.1. U.S. IoT Analytics Market Component breakdown estimates & forecasts, 2020-2030 Deployment breakdown estimates & forecasts, 2020-2030 Application breakdown estimates & forecasts, 2020-2030 Industry Vertical breakdown estimates & forecasts, 2020-2030
9.4.2. Canada IoT Analytics Market
9.5. Europe IoT Analytics Market Snapshot
9.5.1. U.K. IoT Analytics Market
9.5.2. Germany IoT Analytics Market
9.5.3. France IoT Analytics Market
9.5.4. Spain IoT Analytics Market
9.5.5. Italy IoT Analytics Market
9.5.6. Rest of Europe IoT Analytics Market
9.6. Asia-Pacific IoT Analytics Market Snapshot
9.6.1. China IoT Analytics Market
9.6.2. India IoT Analytics Market
9.6.3. Japan IoT Analytics Market
9.6.4. Australia IoT Analytics Market
9.6.5. South Korea IoT Analytics Market
9.6.6. Rest of Asia Pacific IoT Analytics Market
9.7. Latin America IoT Analytics Market Snapshot
9.7.1. Brazil IoT Analytics Market
9.7.2. Mexico IoT Analytics Market
9.8. Middle East & Africa IoT Analytics Market
9.8.1. Saudi Arabia IoT Analytics Market
9.8.2. South Africa IoT Analytics Market
9.8.3. Rest of Middle East & Africa IoT Analytics Market

Chapter 10. Competitive Intelligence
10.1. Key Company SWOT Analysis
10.1.1. Company 1
10.1.2. Company 2
10.1.3. Company 3
10.2. Top Market Strategies
10.3. Company Profiles
10.3.1. Microsoft Corporation Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
10.3.2. Oracle Corporation
10.3.3. Amazon Web Services, Inc.
10.3.4. Cisco Systems, Inc
10.3.5. International Business Machine Corporation
10.3.6. SAP SE
10.3.7. Accenture PLC
10.3.8. Dell Technologies Inc
10.3.9. Google LLC
10.3.10. The Hewlett Packard Enterprise (HPE) Company
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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