Global Data Science Platform Market Research Report 2023

Publication ID:

PB503235384

Publication Date:

March 21, 2023

Pages:

103

Publisher:

MRRPB5

Countries:

Global [1]

USD 2,900.00

IT Services [2]

Computing & Electronics [3]

Description:

In business functions, the logistics segment holds the largest market share and is gaining significant importance among corporates & Enterprises. In the logistics industry, customer satisfaction, global expansion, strong delivery & transport network, and presence of wide global/local presence are the most essential factors. Data scientists apply advanced mathematics and statistics to address numerous business queries that delivers insights to management, thereby maximizing the return on assets and high Returns on Investments (RoI).
Highlights
The global Data Science Platform market was valued at US$ 34610 million in 2022 and is anticipated to reach US$ 106990 million by 2029, witnessing a CAGR of 20.7% during the forecast period 2023-2029. The influence of COVID-19 and the Russia-Ukraine War were considered while estimating market sizes.
The on-premises deployment model has a higher adoption, compared to the on-demand deployment model. The on-premises deployment model provides confidentiality and privacy parameters to the organizational data; hence, most of the organizations are adopting the on-premises deployment model. The Banking, Financial Services, and Insurance (BFSI) segment has shown the largest market share in vertical segment, where data science platform helps financial institutions to cut down on the risks that are likely to arise from the poor quality of data.
Report Scope
This report aims to provide a comprehensive presentation of the global market for Data Science Platform, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Data Science Platform.
The Data Science Platform market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2022 as the base year, with history and forecast data for the period from 2018 to 2029. This report segments the global Data Science Platform market comprehensively. Regional market sizes, concerning products by type, by application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Data Science Platform companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by type, by application, and by regions.
By Company
Microsoft
IBM
Google
Wolfram
Datarobot
Cloudera
Rapidminer
Domino Data Lab
Dataiku
Alteryx
Continuum Analytics
Bridgei2i Analytics
Datarpm
Rexer Analytics
Feature Labs
Segment by Type
On-Premises
On-Demand
Segment by Application
Marketing
Sales
Logistics
Risk
Customer Support
Human Resources
Operations
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Core Chapters
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by type, application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Data Science Platform companies鈥� competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the key companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Data Science Platform Market Size Growth Rate by Type: 2018 VS 2022 VS 2029
1.2.2 On-Premises
1.2.3 On-Demand
1.3 Market by Application
1.3.1 Global Data Science Platform Market Growth by Application: 2018 VS 2022 VS 2029
1.3.2 Marketing
1.3.3 Sales
1.3.4 Logistics
1.3.5 Risk
1.3.6 Customer Support
1.3.7 Human Resources
1.3.8 Operations
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Data Science Platform Market Perspective (2018-2029)
2.2 Data Science Platform Growth Trends by Region
2.2.1 Global Data Science Platform Market Size by Region: 2018 VS 2022 VS 2029
2.2.2 Data Science Platform Historic Market Size by Region (2018-2023)
2.2.3 Data Science Platform Forecasted Market Size by Region (2024-2029)
2.3 Data Science Platform Market Dynamics
2.3.1 Data Science Platform Industry Trends
2.3.2 Data Science Platform Market Drivers
2.3.3 Data Science Platform Market Challenges
2.3.4 Data Science Platform Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Data Science Platform Players by Revenue
3.1.1 Global Top Data Science Platform Players by Revenue (2018-2023)
3.1.2 Global Data Science Platform Revenue Market Share by Players (2018-2023)
3.2 Global Data Science Platform Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Data Science Platform Revenue
3.4 Global Data Science Platform Market Concentration Ratio
3.4.1 Global Data Science Platform Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Data Science Platform Revenue in 2022
3.5 Data Science Platform Key Players Head office and Area Served
3.6 Key Players Data Science Platform Product Solution and Service
3.7 Date of Enter into Data Science Platform Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Data Science Platform Breakdown Data by Type
4.1 Global Data Science Platform Historic Market Size by Type (2018-2023)
4.2 Global Data Science Platform Forecasted Market Size by Type (2024-2029)
5 Data Science Platform Breakdown Data by Application
5.1 Global Data Science Platform Historic Market Size by Application (2018-2023)
5.2 Global Data Science Platform Forecasted Market Size by Application (2024-2029)
6 North America
6.1 North America Data Science Platform Market Size (2018-2029)
6.2 North America Data Science Platform Market Growth Rate by Country: 2018 VS 2022 VS 2029
6.3 North America Data Science Platform Market Size by Country (2018-2023)
6.4 North America Data Science Platform Market Size by Country (2024-2029)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Data Science Platform Market Size (2018-2029)
7.2 Europe Data Science Platform Market Growth Rate by Country: 2018 VS 2022 VS 2029
7.3 Europe Data Science Platform Market Size by Country (2018-2023)
7.4 Europe Data Science Platform Market Size by Country (2024-2029)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Data Science Platform Market Size (2018-2029)
8.2 Asia-Pacific Data Science Platform Market Growth Rate by Region: 2018 VS 2022 VS 2029
8.3 Asia-Pacific Data Science Platform Market Size by Region (2018-2023)
8.4 Asia-Pacific Data Science Platform Market Size by Region (2024-2029)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Data Science Platform Market Size (2018-2029)
9.2 Latin America Data Science Platform Market Growth Rate by Country: 2018 VS 2022 VS 2029
9.3 Latin America Data Science Platform Market Size by Country (2018-2023)
9.4 Latin America Data Science Platform Market Size by Country (2024-2029)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Data Science Platform Market Size (2018-2029)
10.2 Middle East & Africa Data Science Platform Market Growth Rate by Country: 2018 VS 2022 VS 2029
10.3 Middle East & Africa Data Science Platform Market Size by Country (2018-2023)
10.4 Middle East & Africa Data Science Platform Market Size by Country (2024-2029)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Microsoft
11.1.1 Microsoft Company Detail
11.1.2 Microsoft Business Overview
11.1.3 Microsoft Data Science Platform Introduction
11.1.4 Microsoft Revenue in Data Science Platform Business (2018-2023)
11.1.5 Microsoft Recent Development
11.2 IBM
11.2.1 IBM Company Detail
11.2.2 IBM Business Overview
11.2.3 IBM Data Science Platform Introduction
11.2.4 IBM Revenue in Data Science Platform Business (2018-2023)
11.2.5 IBM Recent Development
11.3 Google
11.3.1 Google Company Detail
11.3.2 Google Business Overview
11.3.3 Google Data Science Platform Introduction
11.3.4 Google Revenue in Data Science Platform Business (2018-2023)
11.3.5 Google Recent Development
11.4 Wolfram
11.4.1 Wolfram Company Detail
11.4.2 Wolfram Business Overview
11.4.3 Wolfram Data Science Platform Introduction
11.4.4 Wolfram Revenue in Data Science Platform Business (2018-2023)
11.4.5 Wolfram Recent Development
11.5 Datarobot
11.5.1 Datarobot Company Detail
11.5.2 Datarobot Business Overview
11.5.3 Datarobot Data Science Platform Introduction
11.5.4 Datarobot Revenue in Data Science Platform Business (2018-2023)
11.5.5 Datarobot Recent Development
11.6 Cloudera
11.6.1 Cloudera Company Detail
11.6.2 Cloudera Business Overview
11.6.3 Cloudera Data Science Platform Introduction
11.6.4 Cloudera Revenue in Data Science Platform Business (2018-2023)
11.6.5 Cloudera Recent Development
11.7 Rapidminer
11.7.1 Rapidminer Company Detail
11.7.2 Rapidminer Business Overview
11.7.3 Rapidminer Data Science Platform Introduction
11.7.4 Rapidminer Revenue in Data Science Platform Business (2018-2023)
11.7.5 Rapidminer Recent Development
11.8 Domino Data Lab
11.8.1 Domino Data Lab Company Detail
11.8.2 Domino Data Lab Business Overview
11.8.3 Domino Data Lab Data Science Platform Introduction
11.8.4 Domino Data Lab Revenue in Data Science Platform Business (2018-2023)
11.8.5 Domino Data Lab Recent Development
11.9 Dataiku
11.9.1 Dataiku Company Detail
11.9.2 Dataiku Business Overview
11.9.3 Dataiku Data Science Platform Introduction
11.9.4 Dataiku Revenue in Data Science Platform Business (2018-2023)
11.9.5 Dataiku Recent Development
11.10 Alteryx
11.10.1 Alteryx Company Detail
11.10.2 Alteryx Business Overview
11.10.3 Alteryx Data Science Platform Introduction
11.10.4 Alteryx Revenue in Data Science Platform Business (2018-2023)
11.10.5 Alteryx Recent Development
11.11 Continuum Analytics
11.11.1 Continuum Analytics Company Detail
11.11.2 Continuum Analytics Business Overview
11.11.3 Continuum Analytics Data Science Platform Introduction
11.11.4 Continuum Analytics Revenue in Data Science Platform Business (2018-2023)
11.11.5 Continuum Analytics Recent Development
11.12 Bridgei2i Analytics
11.12.1 Bridgei2i Analytics Company Detail
11.12.2 Bridgei2i Analytics Business Overview
11.12.3 Bridgei2i Analytics Data Science Platform Introduction
11.12.4 Bridgei2i Analytics Revenue in Data Science Platform Business (2018-2023)
11.12.5 Bridgei2i Analytics Recent Development
11.13 Datarpm
11.13.1 Datarpm Company Detail
11.13.2 Datarpm Business Overview
11.13.3 Datarpm Data Science Platform Introduction
11.13.4 Datarpm Revenue in Data Science Platform Business (2018-2023)
11.13.5 Datarpm Recent Development
11.14 Rexer Analytics
11.14.1 Rexer Analytics Company Detail
11.14.2 Rexer Analytics Business Overview
11.14.3 Rexer Analytics Data Science Platform Introduction
11.14.4 Rexer Analytics Revenue in Data Science Platform Business (2018-2023)
11.14.5 Rexer Analytics Recent Development
11.15 Feature Labs
11.15.1 Feature Labs Company Detail
11.15.2 Feature Labs Business Overview
11.15.3 Feature Labs Data Science Platform Introduction
11.15.4 Feature Labs Revenue in Data Science Platform Business (2018-2023)
11.15.5 Feature Labs Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details

Companies Mentioned:

Microsoft
IBM
Google
Wolfram
Datarobot
Cloudera
Rapidminer
Domino Data Lab
Dataiku
Alteryx
Continuum Analytics
Bridgei2i Analytics
Datarpm
Rexer Analytics
Feature Labs

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