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市場調査レポート
商品コード
1658036
IoTアナリティクス市場規模、シェア、成長分析:タイプ別、コンポーネント別、組織規模別、展開モード別、用途別、最終用途産業別、地域別 - 産業予測 2025~2032年IoT Analytics Market Size, Share, and Growth Analysis, By Type, By Component, By Organization Size, By Deployment Mode, By Application, By End-Use Industry, By Region - Industry Forecast 2025-2032 |
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IoTアナリティクス市場規模、シェア、成長分析:タイプ別、コンポーネント別、組織規模別、展開モード別、用途別、最終用途産業別、地域別 - 産業予測 2025~2032年 |
出版日: 2025年02月16日
発行: SkyQuest
ページ情報: 英文 197 Pages
納期: 3~5営業日
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IoTアナリティクスの市場規模は2023年に1,209億3,000万米ドルで、2024年の1,439億1,000万米ドルから2032年には5,787億米ドルに拡大し、予測期間中(2025年~2032年)のCAGRは19.0%で成長する見通しです。
世界のモノのインターネット(IoT)アナリティクス市場は、複数の産業でIoT技術の導入が増加していることを背景に、著しい成長を遂げています。IoTで生成されるデータの急増により、意味のある洞察を引き出すための高度なアナリティクスに対する需要が高まり、企業は業務効率の向上、リソース利用の最適化、情報に基づいた意思決定を行えるようになっています。とはいえ、データセキュリティの懸念や、多様なIoTデータセットの統合に伴う複雑さなどの課題が、成長の妨げになる可能性もあります。同市場は、予測分析やリアルタイム分析など、幅広い分析ソリューションを特徴としています。北米は技術の進歩により市場をリードしているが、アジア太平洋地域はIoT導入の拡大により急速な成長を遂げています。特に、AIと機械学習のIoTアナリティクスへの統合は、データ処理能力と予測機能を強化しています。
IoT Analytics Market size was valued at USD 120.93 billion in 2023 and is poised to grow from USD 143.91 billion in 2024 to USD 578.7 billion by 2032, growing at a CAGR of 19.0% during the forecast period (2025-2032).
The global Internet of Things (IoT) Analytics market is undergoing significant growth, fueled by the increasing implementation of IoT technologies across multiple industries. The surge in IoT-generated data has heightened the demand for advanced analytics to extract meaningful insights, enabling businesses to enhance operational efficiency, optimize resource use, and make informed decisions. Nonetheless, challenges such as data security concerns and the complexities involved in integrating diverse IoT datasets may hinder growth. The market features a wide array of analytics solutions, including predictive and real-time analytics. While North America leads the market due to technological advancements, the Asia-Pacific region is experiencing rapid growth thanks to expanding IoT deployments. Notably, the integration of AI and machine learning into IoT Analytics is enhancing data processing capabilities and predictive functions.
Top-down and bottom-up approaches were used to estimate and validate the size of the IoT Analytics market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
IoT Analytics Market Segments Analysis
Global IoT Analytics Market is segmented by Type, Component, Organization Size, Deployment Mode, Application, End-Use Industry and region. Based on Type, the market is segmented into Descriptive Analytics, Diagnostic Analytics, Predictive Analytics and Prescriptive Analytics. Based on Component, the market is segmented into Software and Services. Based on Organization Size, the market is segmented into Small and Medium Enterprises (SMEs) and Large Enterprises. Based on Deployment Mode, the market is segmented into On-Premises and Cloud-Based. Based on Application, the market is segmented into Predictive Maintenance, Asset Management, Inventory Management,Energy Management, Security and Emergency Management and Sales and Customer Management. Based on End-Use Industry, the market is segmented into Manufacturing, Healthcare, Retail, Transportation and Logistics, Energy and Utilities, Government and Defense and Others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the IoT Analytics Market
The rapid growth of Internet of Things (IoT) devices is creating vast amounts of data, which in turn drives the need for sophisticated analytics to uncover valuable insights. Various organizations across multiple sectors are harnessing IoT Analytics to transform this data into actionable intelligence, thereby improving their decision-making processes. The rising emphasis on operational efficiency, predictive maintenance, and real-time analysis is fueling the adoption of IoT Analytics, particularly within industries such as manufacturing, healthcare, and logistics. This increasing reliance on data-driven insights highlights the critical role of IoT Analytics in optimizing performance and enhancing overall business strategies.
Restraints in the IoT Analytics Market
A significant constraint in the IoT Analytics market is the intricacy involved in integrating various IoT datasets, which arises from the diverse types of devices and platforms present in the IoT ecosystem. This challenge of interoperability can obstruct smooth data flow and analysis, thereby diminishing the effectiveness of IoT Analytics solutions. Additionally, concerns regarding data security and privacy represent another major hurdle, as the vast amounts of sensitive information generated by IoT devices raise fears about unauthorized access and potential data breaches. These factors collectively impede the advancement and adoption of effective IoT Analytics frameworks in the market.
Market Trends of the IoT Analytics Market
The IoT Analytics market is witnessing a significant trend towards edge analytics, driven by the need for real-time insights and reduced latency. Organizations are increasingly prioritizing data processing closer to the source, allowing for faster decision-making and improved operational efficiency. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) within IoT Analytics solutions is transforming data analysis capabilities, enabling more sophisticated and predictive insights. This convergence of edge analytics with advanced AI and ML technologies is not only enhancing data interpretation but also paving the way for innovative applications across various sectors, solidifying IoT Analytics as a vital market component.