Resolving the Agriculture Sector’s Issues with the Help of Data Science

Introduction

Market Overview

The global data science platform market is estimated to reach a value of USD 354 billion by 20207, with a CAGR of 33.5% during the forecast period 2020–2027. With the advent of the fourth industrial revolution, technologies, including data science and artificial intelligence, have entrenched deeper roots within all the commercial and industrial sectors, thereby widening the scope of the data science platform market during the forecast period.  The influence is not restrained to a single sector or industry; data science has gained a colossal adoption rate spanning prominent sectors right from manufacturing, telecommunication to retail and media and entertainment.  Below table portrays data science proficiency based on various industries:

Segmentation Insights

Agriculture

The agriculture sector faces constant challenges in terms of climate changes, water scarcity, and others, resulting in the lack of yield of crops and food. The integration of data analytics will result in a three-fold growth rate to agriculture, thereby contributing a significant amount to the country’s GDP. Data can help in predicting the outcome of a growing season, target a pest or crop disease problem, and more.

Competitive Players

1. IBM Corporation
2. Microsoft Corporation
3. Alphabet Inc.
4. Altair Engineering Inc.
5. Alteryx Inc.
6. MathWorks
7. SAS Institute Inc.
8. RapidMiner Inc.
9. Cloudera Inc.
10. Anaconda Inc.
11. Wolfram
12. Dataiku
13. Civis Analytics
14. H2O.ai
15. Domino Data Lab Inc.
16. RStudio Inc.
17. Rapid Insight
18. DataRobot Inc.
19. Rexer Analytics
20. SAP
21. Databricks

Recent Developments

Recent Developments

• June 2023- E2E Networks, a hyperscaler company focused on artificial intelligence (AI), introduced Tir, a sophisticated Jupyter Notebook Framework designed specifically for data scientists. Tir aims to simplify the process of constructing and training AI models. Tir enables data scientists to overcome obstacles related to deployment, data transmission, Linux administration, and DevOps.
• August 2023- Google and Deloitte collaborated to integrate data science and marketing using AI.

Segmentation

1. By Component
   1. Platform
   2. Services
2. By Deployment Type
   1. On-premise
   2. Cloud
3. By Organization Size
   1. Small and Medium Enterprises (SMEs)
   2. Large Enterprises
4. By Application
   1. Marketing & Sales
   2. Fraud Detection
   3. Risk Management
   4. Supply Chain Management
   5. Customer Service
   6. Others
   7. BFSI
   8. Healthcare
   9. Retail