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).
Scope of the Report:
This report studies the Data Science Platform market status and outlook of Global and major regions, from angles of players, countries, product types and end industries; this report analyzes the top players in global market, and splits the Data Science Platform market by product type and applications/end industries.
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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.
The global Data Science Platform market is valued at xx million USD in 2017 and is expected to reach xx million USD by the end of 2023, growing at a CAGR of 35.8% between 2017 and 2023.
The Asia-Pacific will occupy for more market share in following years, especially in China, also fast growing India and Southeast Asia regions.
North America, especially The United States, will still play an important role which cannot be ignored. Any changes from United States might affect the development trend of Data Science Platform.
Europe also play important roles in global market, with market size of xx million USD in 2017 and will be xx million USD in 2023, with a CAGR of xx%.
Market Segment by Companies, this report covers
Microsoft
IBM
Wolfram
Datarobot
Cloudera
Rapidminer
Domino Data Lab
Dataiku
Alteryx
Continuum Analytics
Bridgei2i Analytics
Datarpm
Rexer Analytics
Feature Labs
Market Segment by Regions, regional analysis covers
North America (United States, Canada and Mexico)
Europe (Germany, France, UK, Russia and Italy)
Asia-Pacific (China, Japan, Korea, India and Southeast Asia)
South America (Brazil, Argentina, Colombia)
Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)
Market Segment by Type, covers
On-Premises
On-Demand
Market Segment by Applications, can be divided into
Marketing
Sales
Logistics
Risk
Customer Support
Human Resources
Operations
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Table Of Contents – Major Key Points
1 Data Science Platform Market Overview
1.1 Product Overview and Scope of Data Science Platform
1.2 Classification of Data Science Platform by Types
1.2.1 Global Data Science Platform Revenue Comparison by Types (2017-2023)
1.2.2 Global Data Science Platform Revenue Market Share by Types in 2017
1.2.3 On-Premises
1.2.4 On-Demand
1.3 Global Data Science Platform Market by Application
1.3.1 Global Data Science Platform Market Size and Market Share Comparison by Applications (2013-2023)
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 Global Data Science Platform Market by Regions
1.4.1 Global Data Science Platform Market Size (Million USD) Comparison by Regions (2013-2023)
1.4.1 North America (USA, Canada and Mexico) Data Science Platform Status and Prospect (2013-2023)
1.4.2 Europe (Germany, France, UK, Russia and Italy) Data Science Platform Status and Prospect (2013-2023)
1.4.3 Asia-Pacific (China, Japan, Korea, India and Southeast Asia) Data Science Platform Status and Prospect (2013-2023)
1.4.4 South America (Brazil, Argentina, Colombia) Data Science Platform Status and Prospect (2013-2023)
1.4.5 Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa) Data Science Platform Status and Prospect (2013-2023)
1.5 Global Market Size of Data Science Platform (2013-2023)
2 Manufacturers Profiles
2.1 Microsoft
2.1.1 Business Overview
2.1.2 Data Science Platform Type and Applications
2.1.2.1 Product A
2.1.2.2 Product B
2.1.3 Microsoft Data Science Platform Revenue, Gross Margin and Market Share (2016-2017)
2.2 IBM
2.2.1 Business Overview
2.2.2 Data Science Platform Type and Applications
2.2.2.1 Product A
2.2.2.2 Product B
2.2.3 IBM Data Science Platform Revenue, Gross Margin and Market Share (2016-2017)
2.3 Google
2.3.1 Business Overview
2.3.2 Data Science Platform Type and Applications
2.3.2.1 Product A
2.3.2.2 Product B
2.3.3 Google Data Science Platform Revenue, Gross Margin and Market Share (2016-2017)
2.4 Wolfram
2.4.1 Business Overview
2.4.2 Data Science Platform Type and Applications
2.4.2.1 Product A
2.4.2.2 Product B
2.4.3 Wolfram Data Science Platform Revenue, Gross Margin and Market Share (2016-2017)
2.5 Datarobot
2.5.1 Business Overview
2.5.2 Data Science Platform Type and Applications
2.5.2.1 Product A
2.5.2.2 Product B
2.5.3 Datarobot Data Science Platform Revenue, Gross Margin and Market Share (2016-2017)
2.6 Cloudera
2.6.1 Business Overview
2.6.2 Data Science Platform Type and Applications
2.6.2.1 Product A
2.6.2.2 Product B
2.6.3 Cloudera Data Science Platform Revenue, Gross Margin and Market Share (2016-2017)
2.7 Rapidminer
2.7.1 Business Overview
2.7.2 Data Science Platform Type and Applications
2.7.2.1 Product A
2.7.2.2 Product B
2.7.3 Rapidminer Data Science Platform Revenue, Gross Margin and Market Share (2016-2017)
Continued……
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