"Big Data Analytics in Agriculture Market – Industry Trends and Forecast to 2030
Global Big Data Analytics in Agriculture Market, By Type (Capturing Data, Storing Data, Sharing Data, Analyzing Data, and Others), Application (Crop Production, Farm Equipment, Weather, and Chemicals), End users (Farmers, Agriculture Regulatory Bodies, Weather Forecast, Agrochemical and Farm Equipment Industries) – Industry Trends and Forecast to 2030.
Data Bridge Market Research analyses that the global big data analytics in agriculture market which was USD 1.24 billion in 2022, is expected to reach USD 3.95 billion by 2030, and is expected to undergo a CAGR of 15.60% during the forecast period of 2023 to 2030. “Capturing data” dominates the type segment of the global big data analytics in agriculture market because data is the foundational element that fuels the entire analytics process. In addition to the insights on market scenarios such as market value, growth rate, segmentation, geographical coverage, and major players, the market reports curated by the Data Bridge Market Research also include in-depth expert analysis, geographically represented company-wise production and capacity, network layouts of distributors and partners, detailed and updated price trend analysis and deficit analysis of supply chain and demand.
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Gathering data from various sources in agriculture, such as sensors, satellites, drones, weather stations, and farm equipment. This data can include information about soil conditions, weather patterns, crop growth, livestock health, and more. Combining and integrating data from multiple sources and formats into a unified and structured dataset for analysis. This may involve data cleansing and transformation to ensure data quality. Big data analytics in agriculture aims to enhance productivity, reduce costs, increase sustainability, and contribute to global food security by harnessing the potential of data to make more informed and precise decisions throughout the agricultural value chain.
**Segments**
- **Application:** In the Big Data Analytics in Agriculture market, the application segment is a crucial factor driving growth. It includes precision farming, livestock monitoring, yield monitoring, soil health monitoring, inventory management, and others. Precision farming, in particular, is experiencing significant demand due to the need for optimized resource usage and increasing productivity in the agriculture sector.
- **Deployment:** Another important segment of the Big Data Analytics in Agriculture market is deployment. It involves on-premise deployment and cloud-based deployment. The cloud-based deployment is gaining traction due to its scalability, flexibility, and cost-effectiveness. It allows farmers and agricultural organizations to access real-time data and insights from anywhere, leading to better decision-making.
- **Component:** The component segment includes software and services. Software solutions play a vital role in processing and analyzing large volumes of agricultural data efficiently. On the other hand, services such as consulting, training, and support are essential for the successful implementation and operation of big data analytics solutions in agriculture.
**Market Players**
- **IBM Corporation:** IBM offers advanced big data analytics solutions for the agriculture sector, enabling farmers to make data-driven decisions to improve crop yield and reduce operational costs.
- **AGCO Corporation:** AGCO provides precision farming technologies that leverage big data analytics to enhance agricultural productivity and sustainability.
- **Deere & Company:** Deere & Company offers integrated solutions that combine data analytics with precision agriculture techniques to help farmers optimize their operations and maximize yield.
- **BASF SE:** BASF SE focuses on developing innovative big data analytics solutions for agriculture, including crop protection and digital farming tools to support sustainable agricultural practices.
- **Oracle Corporation:** Oracle Corporation provides cloud-based big data analytics platforms tailored for the agriculture industry, allowing farmers to harness the power of data for better decision-making.
In conclusion, the Big Data Analytics in Agriculture market is witnessing significant growth driven by factors such as the rising demand for precision farming, advancement in technology, and the need for sustainable agriculturalThe Big Data Analytics in Agriculture market is experiencing notable growth, with various segments contributing to its expansion. The application segment, which encompasses precision farming, livestock monitoring, yield monitoring, soil health monitoring, and inventory management, is a key driver of market growth. Precision farming, in particular, is gaining importance as agricultural stakeholders seek optimized resource utilization and increased productivity. The deployment segment also plays a crucial role in market dynamics, with cloud-based deployment garnering significant attention due to its scalability, flexibility, and cost-effectiveness. This deployment option enables real-time data access and insights, empowering farmers and agricultural organizations to make informed decisions more efficiently.
Moreover, the component segment of the Big Data Analytics in Agriculture market comprises software and services. Software solutions are instrumental in processing and analyzing large volumes of agricultural data effectively, enhancing decision-making capabilities for stakeholders. Services such as consulting, training, and support are vital for the successful implementation and operation of big data analytics solutions in the agriculture sector, underscoring the importance of a comprehensive approach to technology adoption.
Several market players are actively contributing to the growth and development of the Big Data Analytics in Agriculture market. Companies such as IBM Corporation, AGCO Corporation, Deere & Company, BASF SE, and Oracle Corporation offer advanced solutions tailored to the unique needs of the agriculture industry. IBM's data analytics solutions enable data-driven decision-making for improved crop yield and operational efficiency, while AGCO Corporation focuses on precision farming technologies to enhance agricultural productivity and sustainability. Deere & Company provides integrated solutions that combine data analytics with precision agriculture techniques, aiming to optimize farming operations and maximize yield. BASF SE is dedicated to developing innovative big data analytics solutions for agriculture, emphasizing crop protection and digital farming tools to support sustainable agricultural practices. Oracle Corporation offers cloud-based big data analytics platforms specifically designed for the agriculture sector, empowering farmers to leverage data for better decision-making.
In conclusion, the Big Data Analytics in Agriculture market is poised for significant growth, driven by factors such as the increasing demand for precision**Global Big Data Analytics in Agriculture Market Analysis**
- **Type:** The global Big Data Analytics in Agriculture market can be segmented by type into capturing data, storing data, sharing data, analyzing data, and others. Capturing data involves collecting information from various sources, such as sensors and IoT devices, to create a comprehensive dataset for analysis. Storing data refers to the management and organization of large volumes of agricultural data to ensure accessibility and security. Sharing data entails the exchange of insights and information among stakeholders in the agriculture industry to facilitate collaborative decision-making. Analyzing data is a critical process that involves extracting valuable insights and trends from raw data to support strategic planning and operational improvements.
- **Application:** The application segment of the global Big Data Analytics in Agriculture market includes crop production, farm equipment, weather, and chemicals. Crop production applications leverage data analytics to optimize farming practices, improve crop yield, and enhance overall agricultural productivity. Farm equipment applications focus on utilizing data-driven insights to enhance the performance and efficiency of agricultural machinery and equipment. Weather applications involve the analysis of climatic data to predict weather patterns and mitigate risks associated with adverse conditions. Chemicals applications utilize big data analytics to enhance the development and distribution of agrochemical products for optimized agricultural outcomes.
- **End Users:** The end-user segment of the global Big Data Analytics in Agriculture market comprises farmers, agriculture regulatory bodies, weather forecast organizations, agrochemical industries, and farm equipment industries. Farmers leverage data analytics tools to make informed decisions regarding crop management
The Big Data Analytics in Agriculture market research report displays a comprehensive study on production capacity, consumption, import and export for all the major regions across the globe. The target audience considered for this market study mainly consists of Key consulting companies & advisors, Large, medium, and small-sized enterprises, Venture capitalists, Value-added resellers (VARs), Third-party knowledge providers, Investment bankers, and Investors. This global market analysis report is the believable source for gaining the market research that will exponentially accelerate the business growth. The top notch Big Data Analytics in Agriculture market report is the best option to acquire a professional in-depth study on the current state for the market.
Table of Contents: Big Data Analytics in Agriculture Market
1 Introduction
2 Global Big Data Analytics in Agriculture Market Segmentation
3 Executive Summary
4 Premium Insight
5 Market Overview
6 Big Data Analytics in Agriculture Market, by Product Type
7 Big Data Analytics in Agriculture Market, by Modality
8 Big Data Analytics in Agriculture Market, by Type
9 Big Data Analytics in Agriculture Market, by Mode
10 Big Data Analytics in Agriculture Market, by End User
12 Big Data Analytics in Agriculture Market, by Geography
12 Big Data Analytics in Agriculture Market, Company Landscape
13 Swot Analysis
14 Company Profiles
Countries Studied:
- North America (Argentina, Brazil, Canada, Chile, Colombia, Mexico, Peru, United States, Rest of Americas)
- Europe (Austria, Belgium, Denmark, Finland, France, Germany, Italy, Netherlands, Norway, Poland, Russia, Spain, Sweden, Switzerland, United Kingdom, Rest of Europe)
- Middle-East and Africa (Egypt, Israel, Qatar, Saudi Arabia, South Africa, United Arab Emirates, Rest of MEA)
- Asia-Pacific (Australia, Bangladesh, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Sri Lanka, Thailand, Taiwan, Rest of Asia-Pacific)
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