"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.
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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.
**Segments**
- **Solution**: Big data analytics solutions help in analyzing and managing large sets of data efficiently, providing insights for better decision-making in agricultural operations. These solutions can include tools for data collection, storage, analysis, and visualization.
- **Application**: Big data analytics in agriculture can be applied in various areas such as crop management, soil monitoring, weather forecasting, precision farming, livestock management, and supply chain optimization. These applications help farmers optimize their resources and increase productivity.
- **Deployment**: The deployment of big data analytics solutions in agriculture can be on-premises or cloud-based, depending on the specific needs and preferences of the users. Cloud-based deployments offer scalability and accessibility advantages, while on-premises deployments provide greater control over data security.
- **End-User**: The end-users of big data analytics in agriculture can include large farms, agribusiness companies, research institutions, government agencies, and agricultural cooperatives. Each end-user segment has unique requirements and challenges that can be addressed through tailored big data analytics solutions.
**Market Players**
- **IBM Corporation**: IBM offers big data analytics solutions for agriculture that focus on enabling precision farming, crop management, and supply chain optimization. Their platform integrates data from various sources to provide actionable insights for farmers.
- **Microsoft Corporation**: Microsoft provides cloud-based big data analytics solutions for agriculture, helping users leverage advanced analytics, artificial intelligence, and machine learning capabilities for improving farm operations.
- **SAP SE**: SAP offers integrated big data analytics tools for agriculture that cover a wide range of applications such as farm management, crop monitoring, and predictive analytics. Their solutions aim to enhance productivity and sustainability in agriculture.
- **Oracle Corporation**: Oracle's big data analytics solutions for agriculture focus on data management, analysis, and visualization, empowering users to make informed decisions based on real-time insights.
- **Accenture**: Accenture provides consulting services and customized big data analytics solutions for agriculture, helping clients unlock the full potential of their data assets and drive innovationThe big data analytics market in agriculture is witnessing significant growth and innovation, driven by the increasing demand for precision farming, sustainable agricultural practices, and efficient resource management. Market players like IBM Corporation, Microsoft Corporation, SAP SE, Oracle Corporation, and Accenture are at the forefront of providing advanced analytics solutions tailored to the unique needs of the agriculture sector. These companies offer a range of tools and services that enable farmers, agribusinesses, and other stakeholders to harness the power of data for better decision-making and improved operational efficiency.
IBM Corporation stands out in the market with its comprehensive big data analytics solutions that focus on precision farming, crop management, and supply chain optimization. By integrating data from multiple sources and leveraging advanced analytics techniques, IBM helps farmers make informed decisions that drive productivity and sustainability. Microsoft Corporation, on the other hand, emphasizes cloud-based solutions that enable users to access cutting-edge analytics, artificial intelligence, and machine learning capabilities for optimizing farm operations. This cloud-based approach offers scalability and flexibility, critical for modern agricultural operations.
SAP SE is another key player in the big data analytics market for agriculture, offering integrated solutions for farm management, crop monitoring, and predictive analytics. SAP's tools are designed to enhance productivity and sustainability by providing actionable insights that drive operational efficiencies. Oracle Corporation focuses on data management, analysis, and visualization, empowering users to make real-time decisions based on accurate and up-to-date information. By leveraging Oracle's solutions, agricultural stakeholders can improve resource allocation, crop yields, and overall performance.
Accenture, as a leading consulting firm, plays a crucial role in the big data analytics market for agriculture by providing tailored solutions and services that help clients unlock the full potential of their data assets. By combining industry expertise with advanced analytics capabilities, Accenture assists agricultural organizations in driving innovation, improving decision-making processes, and gaining a competitive edge in the market. Overall, the collaboration between market players like IBM, Microsoft, SAP, Oracle, and Accenture is shaping the future of agriculture by harness**Global Big Data Analytics in Agriculture Market**
- **Type**: The big data analytics in agriculture market can be segmented based on types of data processing, including capturing data, storing data, sharing data, analyzing data, and other related activities. Each type plays a crucial role in enabling effective data-driven decision-making in agricultural operations.
- **Application**: The applications of big data analytics in agriculture cover a wide range of areas such as crop production, farm equipment management, weather forecasting, and agrochemical usage. These applications help in optimizing resource allocation, improving crop yields, and enhancing overall operational efficiency in the agriculture sector.
- **End Users**: The end users of big data analytics in agriculture include farmers, agriculture regulatory bodies, weather forecasting agencies, agrochemical companies, and farm equipment industries. Each end user segment has unique requirements and benefits from tailored big data analytics solutions to address specific challenges and opportunities.
The global big data analytics in agriculture market is experiencing rapid growth and transformation due to the increasing adoption of data-driven technologies in the agriculture sector. The market is driven by factors such as the need for precision farming, sustainable agricultural practices, and efficient resource management. Market players like IBM Corporation, Microsoft Corporation, SAP SE, Oracle Corporation, and Accenture are leading the innovation in providing advanced analytics solutions tailored to the unique needs of the agriculture industry.
IBM Corporation stands out with its comprehensive solutions focusing on precision farming, crop management, and supply chain optimization. By integrating data from various sources and leveraging advanced analytics
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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