Data Science Platform by Type (Solutions and Services) by End Use (Telecommunication, BFSI, Healthcare, Transport and Logistics, Manufacturing, and Others), Regional Outlook (North America, Europe, Asia-Pacific, LAMEA), Global Opportunity Analysis and Industry Forecast, 2019–2026
- RES4072078
- 140 Pages
- February 2020
- ICT & Media
Market Definition:
Data science involves obtaining meaningful insights from raw and unstructured data which is processed through programming, and analytical and business skills. Data science is the visualization, extraction, preparation and maintenance of information. Data science tools and practices use data for meaningful outcome to support the companies in taking decisions and conceiving strategies. Data science platform is the mix of problem-solving techniques, data filtration method statistics, and other algorithms which help to take the necessary decision.
Market Drivers:
Rising use of data analytical tools is a major driving factor for the growth of the data science platform market. These analytical tools help the organization to take decisions. Data science helps the user to shape, measure and control the data so that it can be helpful to build the strategy for the business for their new proposals. Many companies have a large set of data that are unutilized. With the help of their historical data the analytical tools aid to take the predictive decision for the business.
Market Restrains:
Lack of skilled professionals is the biggest restraint for the data science platform market. Professional Data scientists deal particularly with the company’s data to take major business decisions on the basis of their data, and hence expertise are required to handle the data carefully. The availability of skilled labor it is going to hamper the growth of the data science platform market in the forecast period.
Data Science Platform by Type:
Depending on the type, the market is segmented into services and solution. Service segment is predicted to grow at a CAGR of 32.0% by generating a revenue of $76.0 billion by 2026. Solution segment is predicted to grow at a CAGR of 30.6% by generating a revenue of $148.2 billion by 2026.
Data Science Platform by End use:
Depending on the end use the market is segmented into telecommunication, BFSI, healthcare, transport and logistics, manufacturing, education, retail, government, energy and utilities. BFSI held the largest market share in 2018 by 23%. BFSI segment was $6.09 billion in 2018 and is predicted to grow at a CAGR of 29.4% in the forecast period. Manufacturing is accounted to have the fastest growth rate in the forecast period. Manufacturing is predicted to grow at a CAGR of 31.9% by generating a revenue of $43.28 billion by 2026.
Data Science Platform by Region:
Depending on the region, the market is segmented into North America, Europe, Asia-Pacific and LAMEA. North America market is predicted to grow at a CAGR of 30.1% by generating a revenue of $80.3 billion by 2026. Asia-Pacific region is predicted to grow at a CAGR of 31.9% by generating a revenue of $48.0 billion by 2026.
Key Participants in the data science platform market
The major key players in the market are Microsoft Corporation, Altair Engineering, Inc., IBM Corporation, Anaconda, Inc., Cloudera, Inc., Civis Analytics, Dataiku, Domino Data Lab, Inc., Alphabet Inc. (Google), and Databricks among others.
1.1. Desk Research
1.2. Real time insights and validation
1.3. Forecast model
1.4. Assumptions and forecast parameters
1.4.1. Assumptions
1.4.2. Forecast parameters
1.5. Data sources
1.5.1. Primary
1.5.2. Secondary
2. Executive Summary
2.1. 360° summary
2.2. type trends
2.3. End use trends
3. Market Overview
3.1. Market segmentation & definitions
3.2. Key takeaways
3.2.1. Top investment pockets
3.2.2. Top winning strategies
3.3. Porter’s five forces analysis
3.3.1. Bargaining power of consumers
3.3.2. Bargaining power of suppliers
3.3.3. Threat of new entrants
3.3.4. Threat of substitutes
3.3.5. Competitive rivalry in the market
3.4. Market dynamics
3.4.1. Drivers
3.4.2. Restraints
3.4.3. Opportunities
3.5. Technology landscape
3.6. Regulatory landscape
3.7. Patent landscape
3.8. Strategic overview
4. Data Science Platform, by type
4.1. Service
4.1.1. Market size and forecast, by region, 2017-2028
4.1.2. Comparative market share analysis, 2018 & 2028
4.2. Solution
4.2.1. Market size and forecast, by region, 2017-2028
4.2.2. Comparative market share analysis, 2018 & 2028
5. Data Science Platform, by End use
5.1. Telecommunication
5.1.1. Market size and forecast, by region, 2017-2028
5.1.2. Comparative market share analysis, 2018 & 2028
5.2. BFSI
5.2.1. Market size and forecast, by region, 2017-2028
5.2.2. Comparative market share analysis, 2018 & 2028
5.3. Healthcare
5.3.1. Market size and forecast, by region, 2017-2028
5.3.2. Comparative market share analysis, 2018 & 2028
5.4. Transport and Logistics
5.4.1. Market size and forecast, by region, 2017-2028
5.4.2. Comparative market share analysis, 2018 & 2028
5.5. Manufacturing
5.5.1. Market size and forecast, by region, 2017-2028
5.5.2. Comparative market share analysis, 2018 & 2028
5.6. Others
5.6.1. Market size and forecast, by region, 2017-2028
5.6.2. Comparative market share analysis, 2018 & 2028
6. Data Science Platform, by Region
6.1. North Region
6.1.1. Market size and forecast, by service type, 2017-2028
6.1.2. Market size and forecast, by end-use, 2017-2028
6.1.3. Market size and forecast, by country, 2017-2028
6.1.4. Comparative market share analysis, 2018 & 2028
6.1.5. U.S
6.1.5.1. Market size and forecast, by service type, 2017-2028
6.1.5.2. Market size and forecast, by end-use, 2017-2028
6.1.5.3. Comparative market share analysis, 2018 & 2028
6.1.6. Canada
6.1.6.1. Market size and forecast, by service type, 2017-2028
6.1.6.2. Market size and forecast, by end-use, 2017-2028
6.1.6.3. Comparative market share analysis, 2018 & 2028
6.2. Europe
6.2.1. Market size and forecast, by service type, 2017-2028
6.2.2. Market size and forecast, by end-use, 2017-2028
6.2.3. Market size and forecast, by country, 2017-2028
6.2.4. Comparative market share analysis, 2018 & 2028
6.2.5. UK
6.2.5.1. Market size and forecast, by service type, 2017-2028
6.2.5.2. Market size and forecast, by end-use, 2017-2028
6.2.5.3. Comparative market share analysis, 2018 & 2028
6.2.6. Germany
6.2.6.1. Market size and forecast, by service type, 2017-2028
6.2.6.2. Market size and forecast, by end-use, 2017-2028
6.2.6.3. Comparative market share analysis, 2018 & 2028
6.2.7. France
6.2.7.1. Market size and forecast, by service type, 2017-2028
6.2.7.2. Market size and forecast, by end-use, 2017-2028
6.2.7.3. Comparative market share analysis, 2018 & 2028
6.2.8. Italy
6.2.8.1. Market size and forecast, by service type, 2017-2028
6.2.8.2. Market size and forecast, by end-use, 2017-2028
6.2.8.3. Comparative market share analysis, 2018 & 2028
6.2.9. Rest of Europe
6.2.9.1. Market size and forecast, by service type, 2017-2028
6.2.9.2. Market size and forecast, by end-use, 2017-2028
6.2.9.3. Comparative market share analysis, 2018 & 2028
6.3. Asia-Pacific
6.3.1. Market size and forecast, by service type, 2017-2028
6.3.2. Market size and forecast, by end-use, 2017-2028
6.3.3. Market size and forecast, by country, 2017-2028
6.3.4. Comparative market share analysis, 2018 & 2028
6.3.5. China
6.3.5.1. Market size and forecast, by service type, 2017-2028
6.3.5.2. Market size and forecast, by end-use, 2017-2028
6.3.5.3. Comparative market share analysis, 2018 & 2028
6.3.6. India
6.3.6.1. Market size and forecast, by service type, 2017-2028
6.3.6.2. Market size and forecast, by end-use, 2017-2028
6.3.6.3. Comparative market share analysis, 2018 & 2028
6.3.7. Japan
6.3.7.1. Market size and forecast, by service type, 2017-2028
6.3.7.2. Market size and forecast, by end-use, 2017-2028
6.3.7.3. Comparative market share analysis, 2018 & 2028
6.3.8. South Korea
6.3.8.1. Market size and forecast, by service type, 2017-2028
6.3.8.2. Market size and forecast, by end-use, 2017-2028
6.3.8.3. Comparative market share analysis, 2018 & 2028
6.3.9. Australia
6.3.9.1. Market size and forecast, by service type, 2017-2028
6.3.9.2. Market size and forecast, by end-use, 2017-2028
6.3.9.3. Comparative market share analysis, 2018 & 2028
6.3.10. Rest of Asia Pacific
6.3.10.1. Market size and forecast, by service type, 2017-2028
6.3.10.2. Market size and forecast, by end-use, 2017-2028
6.3.10.3. Comparative market share analysis, 2018 & 2028
6.4. LAMEA
6.4.1. Market size and forecast, by service type, 2017-2028
6.4.2. Market size and forecast, by end-use, 2017-2028
6.4.3. Market size and forecast, by country, 2017-2028
6.4.4. Comparative market share analysis, 2018 & 2028
6.4.5. Middle East
6.4.5.1. Market size and forecast, by service type, 2017-2028
6.4.5.2. Market size and forecast, by end-use, 2017-2028
6.4.5.3. Comparative market share analysis, 2018 & 2028
6.4.6. Africa
6.4.6.1. Market size and forecast, by service type, 2017-2028
6.4.6.2. Market size and forecast, by end-use, 2017-2028
6.4.6.3. Comparative market share analysis, 2018 & 2028
6.4.7. Rest of LAMEA
6.4.7.1. Market size and forecast, by service type, 2017-2028
6.4.7.2. Market size and forecast, by end-use, 2017-2028
6.4.7.3. Comparative market share analysis, 2018 & 2028
7. Company Profiles
7.1. Databricks
7.1.1. Business overview
7.1.2. Financial performance
7.1.3. Product portfolio
7.1.4. Recent strategic moves & developments
7.1.5. SWOT analysis
7.2. Alphabet Inc. (Google)
7.2.1. Business overview
7.2.2. Financial performance
7.2.3. Product portfolio
7.2.4. Recent strategic moves & developments
7.2.5. SWOT analysis
7.3. Domino Data Lab, Inc.,
7.3.1. Business overview
7.3.2. Financial performance
7.3.3. Product portfolio
7.3.4. Recent strategic moves & developments
7.3.5. SWOT analysis
7.4. Dataiku
7.4.1. Business overview
7.4.2. Financial performance
7.4.3. Product portfolio
7.4.4. Recent strategic moves & developments
7.4.5. SWOT analysis
7.5. Civis Analytics
7.5.1. Business overview
7.5.2. Financial performance
7.5.3. Product portfolio
7.5.4. Recent strategic moves & developments
7.5.5. SWOT analysis
7.6. Cloudera, Inc.
7.6.1. Business overview
7.6.2. Financial performance
7.6.3. Product portfolio
7.6.4. Recent strategic moves & developments
7.6.5. SWOT analysis
7.7. Anaconda, Inc.
7.7.1. Business overview
7.7.2. Financial performance
7.7.3. Product portfolio
7.7.4. Recent strategic moves & developments
7.7.5. SWOT analysis
7.8. IBM Corporation
7.8.1. Business overview
7.8.2. Financial performance
7.8.3. Product portfolio
7.8.4. Recent strategic moves & developments
7.8.5. SWOT analysis
7.9. Altair Engineering, Inc.
7.9.1. Business overview
7.9.2. Financial performance
7.9.3. Product portfolio
7.9.4. Recent strategic moves & developments
7.9.5. SWOT analysis
7.10. Microsoft Corporation
7.10.1. Business overview
7.10.2. Financial performance
7.10.3. Product portfolio
7.10.4. Recent strategic moves & developments
7.10.5. SWOT analysis
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