The data science platform market was earlier at USD 10.8 billion in 2020 and now it is expected to grow by USD 31.4 Billion by 2026 at the CAGR of about 81.25%.
Asia-Pacific region is expected to adopt the data science platform significantly with the increment of FDIs, Flexible government policies advocating the growth of digitalization, industrialization and smart city initiatives by various governments that supports utilizing technology.
There are many profound drivers/growth factors for the upbringing of the data science platform market. The use of data science is in the field like data preparation, interactive exploration, and visualization, feature engineering, advanced modeling testing, training, deployment and performance engineering. The use of data science is in nearly every field like agriculture, Electricity, water, healthcare, education, traffic or road accidents, and air pollution. The data is collected for various purposes to manage out the work in a completely organized way and to ease out the process for the growth of any business and advancement in big data technologies to drive the market for the data science platform.
With the help of data science, public health can be improved through wearable trackers that motivate individuals to adopt healthier habits and can alert people to potentially critical health issues the data collected can also improve diagnostic accuracy, accelerate finding cures for specific diseases, or even stop the spread of a virus. Whereas, the data science platform market may tend to get restraints due to the lack of reliability on data science among enterprises, many cases where data cannot be appropriately governed, government rules and regulation have been the major restraint for the market to grow.
The data science platform market is segmented and sub-segmented as follows:
Marketing
Sales
Logistics
Risk
Customer support
Human resources and Operations
On-premises
On demand
Healthcare and life sciences
IT and Telecom
Retail and consumer goods
Media and Entertainment Manufacturing
Transportation and logistics
Energy and Utilities
Government,
Defense and others.
North America
Europe
Asia Pacific
Latin America
Middle-East and Africa
Many industries are growing to utilize analytics and AI in many ways, and this helps in various fields as financial services, consumer product goods, telecom, and healthcare for the make-up of decisions this is what helping the data science platform market to grow and develop even more in the upcoming years.
In 2019, Credit Risk Analytics will deep dive in the Lending algorithm of New to Credit (NTC) using the latest AI/ML tools. While several fintech’s have come up with incremental data enrichment for this segment, Banks & NBFCs will soon see a crystallized logical way of managing NTC customers through advanced analytics.
Deployment of models for real-time use-cases has come into the trend by making 70% of organization spending time on real-time analytics that helps growing and finding correlations and hidden patterns that help business leaders make and take decisions.
Companies leading the Global Data Science Platform Market profiled in the report are:
Microsoft Corporation
IBM Corporation
Google Inc.
Wolfram
DataRobot In.
Rapid Miner Inc.
Domino Data Lab
Dataiku
Alteryx Inc.
Continuum Analytics Inc.
Platforms providing data science software
There are many platforms for data science and machine learning as Alteryx Analytics, h2o.ai, knime analytics platform, rapid miner, SAS, Mathworks Matlab and Simulink, Tibco software, and data bricks unified analytics platform, domino data science platform, Microsoft Azure machine learning studio is the essential platforms for data science.
1. Introduction
1.1 Market Definition
1.2 Scope of the report
1.3 Study Assumptions
1.4 Base Currency, Base Year and Forecast Periods
2. Research Methodology
2.1 Analysis Design
2.2 Research Phases
2.2.1 Secondary Research
2.2.2 Primary Research
2.2.3 Data Modelling
2.2.4 Expert Validation
2.3 Study Timeline
3. Report Overview
3.1 Executive Summary
3.2 Key Inferencees
4. Market Dynamics
4.1 Impact Analysis
4.1.1 Drivers
4.1.2 Restaints
4.1.3 Opportunities
4.2 Regulatory Environment
4.3 Technology Timeline & Recent Trends
5. Competitor Benchmarking Analysis
5.1 Market Share Analysis
5.2 Product Benchmarking
5.3 Regional Presence
5.4 Mergers & Acquistion Landscape
5.5 Joint Ventures & Collaborations
6. Market Segmentation
6.1 Data Science Platform Market , by Business Function
6.1.1 Marketing
6.1.2 Sales
6.1.3 Logistics
6.1.4 Risk
6.1.5 Customer Support
6.1.6 Human Resources
6.1.7 Operations
6.1.8 Market Size Estimations & Forecasts (2021-2026)
6.1.9 Y-o-Y Growth Rate Analysis
6.1.10 Market Attractiveness Index
6.2 Data Science Platform Market , by Deployment Model
6.2.1 Market Size Estimations & Forecasts (2021-2026)
6.2.2 Y-o-Y Growth Rate Analysis
6.2.3 Market Attractiveness Index
6.3 Data Science Platform Market , by Vertical
6.3.1 Market Size Estimations & Forecasts (2021-2026)
6.3.2 Y-o-Y Growth Rate Analysis
6.3.3 Market Attractiveness Index
7. Geographical Landscape
7.1 Global Data Science Platform Market, by Region
7.2 North America - Market Analysis (2021-2026)
7.2.1 By Country
7.2.1.1 USA
7.2.1.2 Canada
7.2.2 By Business Function
7.2.3 By Deployment Model
7.2.4 By Vertical
7.2.5 Y-o-Y Growth Rate Analysis
7.2.6 Market Attractiveness Index
7.3 Europe
7.3.1 By Country
7.3.1.1 UK
7.3.1.2 France
7.3.1.3 Germany
7.3.1.4 Spain
7.3.1.5 Italy
7.3.1.6 Rest of Europe
7.2.2 By Business Function
7.2.3 By Deployment Model
7.2.4 By Vertical
7.2.5 Y-o-Y Growth Rate Analysis
7.2.6 Market Attractiveness Index
7.4 Asia Pacific
7.4.1 By Country
7.4.1.1 China
7.4.1.2 India
7.4.1.3 Japan
7.4.1.4 South Korea
7.4.1.5 South East Asia
7.4.1.6 Australia & NZ
7.4.1.7 Rest of Asia-Pacific
7.2.2 By Business Function
7.2.3 By Deployment Model
7.2.4 By Vertical
7.2.5 Y-o-Y Growth Rate Analysis
7.2.6 Market Attractiveness Index
7.5 Latin America
7.5.1 By Country
7.5.1.1 Brazil
7.5.1.2 Argentina
7.5.1.3 Mexico
7.5.1.4 Rest of Latin America
7.5.2 By Business Function
7.5.3 By Deployment Model
7.5.4 By Vertical
7.5.5 Y-o-Y Growth Rate Analysis
7.5.6 Market Attractiveness Index
7.6 Middle East and Africa
7.6.1 By Country
7.6.1.1 Middle East
7.6.1.2 Africa
7.6.2 By Business Function
7.6.3 By Deployment Model
7.6.4 By Vertical
7.6.5 Y-o-Y Growth Rate Analysis
7.6.6 Market Attractiveness Index
8. Key Player Analysis
8.1 Microsoft Corporation
8.1.1 Business Description
8.1.2 Products/Service
8.1.3 Financials
8.1.4 SWOT Analysis
8.1.5 Recent Developments
8.1.6 Analyst Overview
8.2 IBM Corporation
8.3 Google Inc.
8.4 Wolfram
8.5 DataRobot In.
8.6 Rapid Miner Inc
8.7 Domino Data Lab
8.8 Dataiku
8.9 Alteryx Inc.
8.10 Continuum Analytics Inc.
9. Market Outlook & Investment Opportunities
Appendix
List of Tables
List of Figures
