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Global Big Data Analytics In Agriculture Market Projected to Surpass $2.42 Billion by 2029 with 13.2% Annual Growth
Big Data Analytics In Agriculture Market
The market size of big data analytics in agriculture has seen a swift expansion in the past few years. The anticipated growth from $1.3 billion in 2024 to $1.47 billion in 2025, with a compound annual growth rate (CAGR) of 13.4%, is substantial. Factors contributing to this escalation during the historic period include variations in weather conditions, soil health, crop production, occurrences of pests and diseases, adoption of technology, fluctuations in market prices, and water consumption.
In the upcoming years, the market size of big data analytics in agriculture is predicted to experience swift growth, escalating to $2.42 billion by 2029 with a compound annual growth rate (CAGR) of 13.2%. Factors contributing to the growth during the projected period can be linked to climate shifts, advances in technology, increased population, policy alterations, sustainable practices, the management of pests and diseases, and the availability of resources. The expected period will also see key trends like precision farming, advanced irrigation systems, automatic machinery, drone utilization, genetic alterations, data-based decision making, and the use of blockchain in managing supply chains.
What Are the Forces Behind the Rapid Growth of the Big Data Analytics In Agriculture Market?
The growth of big data analytics in the agriculture market is predicted to be driven by the rising implementation of precision farming. This type of agricultural management uses technology to boost crop production and effectiveness by meticulously observing and reacting to changes in field conditions. Precision farming is gaining popularity due to its potential to improve productivity, lower input costs, and lessen environmental damage through the targeted use of resources. Big data analytics aids precision farming by examining enormous amounts of farming data, thus providing insights for precise decision-making in crop management practices. As an example, in August 2023, a report from the United States Department of Agriculture, a federal agency based in the US, revealed that precision farming adoption in the US was at 25% in 2021, and it increased to 27% in 2023. Furthermore, North Dakota reported the greatest adoption rate of 57%, trailed by states like Illinois, Iowa, Kansas, Nebraska, and South Dakota, all of which reported rates of 49% or more. Consequently, the rise in precision farming adoption will spur the growth of big data analytics in the agriculture market.
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Which Key Market Leaders Are Driving Big Data Analytics In Agriculture Industry Growth?
Major companies operating in the big data analytics in agriculture market are BASF SE, International Business Machines Corporation (IBM), Deere & Company (John Deere), SAP SE, Bayer AG, Yara International ASA, CNH Industrial NV, AGCO Corporation, Corteva Inc., Hexagon AB, Valmont Industries Inc, Trimble Inc, NTT DATA Business Solutions AG, Topcon Positioning Systems Inc, Lindsay Corporation, AeroVironment Inc., Raven Industries Inc, The Climate Corporation, Planet Labs PBC, AG Leader Technology Inc., Farmers Edge Inc, PrecisionHawk Inc., Prospera Technologies, Descartes Labs, Agribotix LLC, AgDNA, OnFarm Systems, Conservis LLC
What Are the Emerging Trends in the Big Data Analytics In Agriculture Industry?
Key players in the big data analytics sector for agriculture are leaning towards strategic collaboration to amplify AI, machine learning, and market visibility. A strategic collaboration often includes multiple organizations pooling their resources, know-how, and efforts to fulfill shared targets or goals. For example, in September 2023, Agrematch., a biotechnology research and artificial intelligence (AI) company based in Israel, teamed up with ICL Group Ltd., an Israel-based agrochemical manufacturing firm, aiming to provide innovative AI for detecting bio stimulants to optimize farming. This joint effort endeavors to maximize crop production, enhance resource efficiency, and endorse sustainable agriculture methods by equipping farmers with accurate, data-led suggestions for utilizing fertilizers and other farming components. Agrematch employs data science and artificial intelligence's prowess, utilizing state-of-the-art machine and deep learning (ML/DL) algorithms, paired with their exclusive database. In addition, they harmonize these technologies with proficiency in biology, chemistry, and agriculture. They have constructed a sturdy predictive AI platform to spur innovation, curtail environmental harm, and aid farmers with resources and knowledge to enhance their yield and sustainability.
What Are the Main Segments in the Big Data Analytics In Agriculture Market?
The big data analytics in agriculture market covered in this report is segmented -
1) By Component: Solution, Services
2) By Type: Capturing Data, Storing Data, Sharing Data, Analyzing Data, Other Types
3) By Application: Chemical, Financial, Weather, Farm Equipment, Crop Production
Subsegments:
1) By Solution: Data Management And Storage Solutions, Data Visualization Tools, Predictive Analytics Solutions, Decision Support Systems, Cloud-Based Solutions, Farm Management Software
2) By Services: Consulting Services, Implementation Services, Training and Support Services, Managed Services, Data Analysis And Reporting Services
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Which Geographic Area Leads the Big Data Analytics In Agriculture Market?
North America was the largest region in the big data analytics in agriculture market in 2023. The regions covered in the big data analytics in agriculture market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What Is Covered In The Big Data Analytics In Agriculture Global Market Report?
- Market Size Analysis: Analyze the Big Data Analytics In Agriculture Market size by key regions, countries, product types, and applications.
- Market Segmentation Analysis: Identify various subsegments within the Big Data Analytics In Agriculture Market for effective categorization.
- Key Player Focus: Focus on key players to define their market value, share, and competitive landscape.
- Growth Trends Analysis: Examine individual growth trends and prospects in the Market.
- Market Contribution: Evaluate contributions of different segments to the overall Big Data Analytics In Agriculture Market growth.
- Growth Drivers: Detail key factors influencing market growth, including opportunities and drivers.
- Industry Challenges: Analyze challenges and risks affecting the Big Data Analytics In Agriculture Market.
- Competitive Developments: Analyze competitive developments, such as expansions, agreements, and new product launches in the market.
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