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Big Data Analytics in Agriculture Market Insights Industry Analysis and Forecasts | Taiwan News


Report Ocean published the latest research report on the Big Data Analytics in Agriculture Market. In order to comprehend a market holistically, a variety of factors must be evaluated, including demographics, business cycles, and microeconomic requirements that pertain precisely to the market under study. In addition, the Big Data Analytics in Agriculture Market study demonstrates a detailed examination of the business state, which represents creative ways for company growth, financial factors such as production value, key regions, and growth rate. [Download Free Sample]

The global big data analytics in agriculture market size was 0.9 billion in 2021. The global big data analytics in the agriculture market is forecast to grow to US$ 1.79 billion by 2030 by registering a compound annual growth rate (CAGR) of 11.6% during the forecast period from 2022 to 2030.

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Big data refers to the vast amount of data gathered for information required to assist an organization with further strategies and decisions. Big Data analytics is gaining significant popularity in the agriculture sector to help farmers tackle problems related to the global population, climate change, and urbanization.

Factors Influencing the Market

The rising adoption of urban farming practices will primarily drive the growth of the global big data analytics in agriculture market during the study period. The market is expected to witness potential opportunities due to the factors like rising population, rising demand for organic crops, etc. Apart from that, large-scale data analysis and AI can help urban farmers enhance their efficiency, which will bring lucrative growth opportunities for big data analytics in agriculture market during the study period.

IoT devices are made to increase the overall productivity of farming. For instance, it is difficult for farmers to control the spread of infection in a herd of thousands of cows. This can be reduced through IoT gadgets designed to evaluate fertility. Thus, it will result in successful breeding. On the flip side, the high costs of big data analytics may limit the adoption of technology in agriculture sector.

Regional Analysis

North America held the largest share in the big data analytics in agriculture market, owing to the contribution of prominent countries like the United States and Canada. Further, the region is home to a myriad number of large farmhouses with the best agricultural equipment. Thus, the growing adoption of advanced technologies is expected to positively contribute to the growth of the big data analytics in agriculture market during the study period.

The Asia-Pacific big data analytics in agriculture market will also record significant growth due to the growing urban population of the region.

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COVID-19 Impact Analysis

Due to the COVID-19 pandemic, farming activities were significantly hampered due to the shortage of laborers. Apart from that, the impact on consumer purchasing power further affected the adoption of big data analytics in agriculture market.

However, due to food safety recalls, consumer demand, and environmental initiatives, agricultural production has come under more scrutiny. According to the Global Food Traceability Center (GFTC), the pandemic has progressively raised the demand for agricultural products as cutting-edge data-driven solutions can help farmers boost their production capacity. Thus, it positively affected the big data analytics in agriculture market.

Competitors in the Market

• Deere & Company

• Taranis

• AgEagle

• Teejet Technologies

• The Climate Corporation

• Trimble

• AGCO Corporation

• AgJunction

• Raven Industries

• AG Leader

• Topcon Positioning Systems

• Descartes Labs

• ec2ce

• Prospera Technologies

• Autonomous Tractor Corporation

• Other Prominent Players

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Market Segmentation

The global big data analytics in agriculture market segmentation focuses on Component, Application, and Region.

By Component

• Solution

• Services

By Application

• Farm Analytics

• Livestock Analytics

• Aquaculture Analytics

By Regional Outlook

● North America

o The U.S.

o Canada

o Mexico

● Europe

▪ Western Europe

o The UK

o Germany

o France

o Italy

o Spain

o Rest of Western Europe

▪ Eastern Europe

o Poland

o Russia

o Rest of Eastern Europe

● Asia Pacific

o China

o India

o Japan

o Australia & New Zealand

o ASEAN

o Rest of Asia Pacific

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● Middle East & Africa (MEA)

o UAE

o Saudi Arabia

o South Africa

o Rest of MEA

● South America

o Brazil

o Argentina

o Rest of South America

Table of Content

Chapter 1: Global Big Data Analytics in Agriculture Industry Overview

Chapter 3: Market Dynamics

Chapter 4: Top Company Profiles

Chapter 5: Global Big Data Analytics in Agriculture market Competition, by Players

Chapter 6: Global Market Size by Regions

Chapter 7: Global Market Segment by Application

Chapter 8: Global Big Data Analytics in Agriculture Industry Segment by Type

Chapter 9: Market Chain, Sourcing Strategy, and Downstream Buyers

Chapter 10: Strategies and key policies by Distributors/Suppliers/Traders

Chapter 11: Key Marketing Strategy Analysis, by Market Vendors

Chapter 12: Market Effect Factors Analysis

Chapter 13: Global Big Data Analytics in Agriculture market Size Forecast (2023-2032).

Continue….

Reasons to Buy This Report

(A) The research provides valuable insights for top administration, policymakers, professionals, product advancements, sales managers, and stakeholders in the market. It helps them make informed decisions and strategize effectively.

(B) The report offers comprehensive analysis of Big Data Analytics in Agriculture market revenues on a global, regional, and country level, projecting trends until 2032. This data allows companies to assess their market share, identify growth opportunities, and explore new markets.

(C) The research includes segmentation of the Big Data Analytics in Agriculture market based on types, applications, technologies, and end-uses. This segmentation enables leaders to plan their products and allocate resources based on the expected growth rates of each segment.

(D) Analysis of the Big Data Analytics in Agriculture market benefits investors by providing insights into market scope, position, key drivers, challenges, restraints, expansion opportunities, and potential threats. This information helps them make informed investment decisions.

(E) The report offers a detailed analysis of competitors, their key strategies, and market positioning. This knowledge allows businesses to better understand the competition and plan their own strategies accordingly.

(F) The study helps evaluate Big Data Analytics in Agriculture business predictions by region, key countries, and top companies, providing valuable information for investment planning and decision-making.

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