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Global Data Science Platform Market (2021 to 2026) - by Component, Deployment, Organization Size, Function, Industry Vertical and Geography

Dublin, Oct. 21, 2021 (GLOBE NEWSWIRE) -- The "Global Data Science Platform Market (2021-2026) by Component, Deployment, Organization Size, Function, Industry Vertical, Geography, Competitive Analysis and the Impact of COVID-19 with Ansoff Analysis" report has been added to ResearchAndMarkets.com's offering.

The Global Data Science Platform Market is estimated to be USD 43.3 Bn in 2021 and is expected to reach USD 73.2 Bn by 2026, growing at a CAGR of 11.07%.

Key factors such as a massive increase in data volume due to increasing digitalization and automation of processes have been a crucial driver in the growth of data science platform. Besides, the enterprises are increasingly focusing on analytical tools for deriving insights into consumer behavior and purchasing patterns. This, in turn, has been shaping their business decisions and strategies to compete in the market. Besides, the adoption of data science platforms has found its way in various industry verticals such as manufacturing, IT, BFSI, retail, etc. All these factors have helped in contributing to the growth of the data science platform market.

However, the costs attached to the deployment of these platforms, along with less workforce with domain expertise capabilities and threats to data privacy, has been a hindrance in the growth of the market.

Market Dynamics

Drivers

  • High Generation of Data Volumes

  • Rising Focus On Data-Driven Decisions

  • Increasing Adoption of Data Science Platforms Across Diversified Industry Verticals

Restraints

  • High Initial Investments

  • Lack of Domain Expertise

  • Data Privacy, Security, and Reliability Concerns

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Opportunities

  • Increasing Adoption of Data-Driven Technologies by Enterprises

  • Increasing Demand for Public Cloud

  • Investments and Funding in Development of Big Data and Related Technologies by Public and Private Sectors

Challenges

  • Stringent Government Rules and Regulations

Segments Covered

By Component, the market is classified as platform and services. Amongst the two, the Platforms segment holds the highest market share. With a rise in digitalization and automation in various processes, data has been at the forefront. With massive data being churned by the enterprises, the availability of data science platforms is proving beneficial to provide real-time insights and streamline the business processes accordingly. Therefore, enterprises are adopting these platforms to bring process uniformity and business efficiency. This has accelerated the demand for the platform segment.

By Deployment, the Cloud-based segment is estimated to hold the highest market share. The cloud-based platforms are comparatively cost-effective and scalable with the ease of deployment. Since they can be accessible with minimum capital requirements, they are considered a resourceful source of deployment in varied industry sectors.

By Organization Size, Large Enterprises hold the highest market share. A data science platform has essential tools such as predictive analytical tools that can help an organization derive insights and provide meaningful business outcomes. The large scale organizations have the financial backing to invest in such solutions and provide an enhanced customer experience. The real-time insights can help these enterprises in improvising their business processes too. Therefore such enterprises hold a higher demand for data science platforms.

By Function, the Marketing And Sales segment is estimated to hold a high market share. The availability of data science platform in marketing and sales has decipher more insights about buyer behaviour patterns, marketing spending, and help the enterprises generate more ROI. The enterprises are also depending on these platforms due to their reliability in services, reducing financial risks, thereby generating higher revenues. Besides, these platforms are capable of providing an enhanced customer experience. This has led to a high adoption rate in the marketing and sales segment resulting in market segment growth.

By Industry Vertical, the BFSI sector adequately implements such platforms for proactively engaging in fraud detection and providing their customers the needed security. The data science platform can help manage customer data, reduce the complexity in operations, and provide insightful data for risk modeling for investment bankers. Also, the banks are often engaged in providing their customer's personalized services, storing massive data. These platforms can be helpful in this regard, thereby supporting the BFSI market segment growth. Besides the BFSI segment, the healthcare segment has also been drawing lucrative opportunities from these platforms. One of the prominent applications has been in the medical imaging segment. These platforms are being used in the diagnostic segment for improving diagnostic accuracy and efficiency.

By Geography, North America is projected to lead the market. The factors attributed to the growth of the market are the presence of capital intensive industries seeking to deploy a data science platform by integrating with their current IT infrastructure to have a competitive edge over the market. The region has a comparatively faster adoption rate to newer technological solutions due to a solid technological infrastructure. This has further led to a rise in the data science platform vendors offering new solutions to the enterprises. All these factors have aided in the growth of the data science platform of this region.

Company Profiles

Some of the companies covered in this report are Microsoft Corporation, IBM Corporation, SAS Institute, Inc., SAP SE, RapidMiner, Inc., Dataiku SAS, Alteryx, Inc., Fair Issac Corporation, MathWorks, Inc., Teradata, Inc, etc.

Competitive Quadrant

The report includes a Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.

Why buy this report?

  • The report offers a comprehensive evaluation of the Global Data Science Platform Market.

  • The report includes in-depth qualitative analysis, verifiable data from authentic sources, and projections about market size. The projections are calculated using proven research methodologies.

  • The report has been compiled through extensive primary and secondary research. The primary research is done through interviews, surveys, and observation of renowned personnel in the industry.

  • The report includes in-depth market analysis using Porter's 5 force model and the Ansoff Matrix. The impact of Covid-19 on the market is also featured in the report.

  • The report also contains the competitive analysis using Competitive Quadrant, the analyst's proprietary competitive positioning tool.

Report Highlights:

  • A complete analysis of the market including parent industry

  • Important market dynamics and trends

  • Market segmentation

  • Historical, current, and projected size of the market based on value and volume

  • Market shares and strategies of key players

  • Recommendations to companies for strengthening their foothold in the market

Key Topics Covered:

1 Report Description

2 Research Methodology

3 Executive Summary

4 Market Overview
4.1 Introduction
4.2 Market Dynamics
4.2.1 Drivers
4.2.2 Restraints
4.2.3 Opportunities
4.2.4 Challenges
4.3 Trends

5 Market Analysis
5.1 Porter's Five Forces Analysis
5.2 Impact of COVID-19
5.3 Ansoff Matrix Analysis

6 Global Data Science Platform Market, By Component
6.1 Introduction
6.2 Platform
6.3 Services
6.3.1 Managed Services
6.3.2 Professional Services
6.3.2.1 Training and Consulting
6.3.2.2 Integration and Deployment
6.3.2.3 Support and Maintenance

7 Global Data Science Platform Market, By Deployment
7.1 Introduction
7.2 Cloud
7.3 On-premises

8 Global Data Science Platform Market, By Organization Size
8.1 Introduction
8.2 Large Enterprises
8.3 Small and Medium-sized Enterprises

9 Global Data Science Platform Market, By Function
9.1 Introduction
9.2 Marketing
9.3 Sales
9.4 Logistics
9.5 Finance and Accounting
9.6 Customer Support
9.7 Others

10 Global Data Science Platform Market, By Industry Verticals
10.1 Introduction
10.2 Banking, Financial Services, and Insurance (BFSI)
10.3 Telecom and IT
10.4 Retail and E-Commerce
10.5 Healthcare and Life sciences
10.6 Manufacturing
10.7 Energy and Utilities
10.8 Media and Entertainment
10.9 Transportation and Logistics
10.10 Government
10.11 Others

11 Global Data Science Platform Market, By Geography
11.1 Introduction
11.2 North America
11.2.1 US
11.2.2 Canada
11.2.3 Mexico
11.3 South America
11.3.1 Brazil
11.3.2 Argentina
11.4 Europe
11.4.1 UK
11.4.2 France
11.4.3 Germany
11.4.4 Italy
11.4.5 Spain
11.4.6 Rest of Europe
11.5 Asia-Pacific
11.5.1 China
11.5.2 Japan
11.5.3 India
11.5.4 Indonesia
11.5.5 Malaysia
11.5.6 South Korea
11.5.7 Australia
11.5.8 Russia
11.5.9 Rest of APAC
11.6 Rest of the World
11.6.1 Qatar
11.6.2 Saudi Arabia
11.6.3 South Africa
11.6.4 United Arab Emirates
11.6.5 Latin America

12 Competitive Landscape
12.1 Competitive Quadrant
12.2 Market Share Analysis
12.3 Competitive Scenario
12.3.1 Mergers & Acquisitions
12.3.2 Agreements, Collaborations, & Partnerships
12.3.3 New Product Launches & Enhancements
12.3.4 Investments & Fundings

13 Company Profiles
13.1 Microsoft Corporation
13.2 IBM Corporation
13.3 Google, Inc
13.4 Wolfram
13.5 DataRobot Inc.
13.6 Sense Inc.
13.7 RapidMiner Inc.
13.8 Domino Data Lab
13.9 Dataiku SAS
13.10 Alteryx, Inc.
13.11 Oracle
13.12 Tibco Software Inc.
13.13 SAS Institute Inc.
13.14 SAP SE
13.15 The Mathworks, Inc.
13.16 Cloudera, Inc.
13.17 H2O.ai
13.18 Fair Issac Corporation
13.19 Teradata, Inc
13.20 Kaggle Inc.,
13.21 Micropole S.A.
13.22 Continuum Analytics, Inc.
13.23 C&F Insight technology solutions
13.24 Civis Analytics, Inc.
13.25 VMware Inc
13.26 Alpine Data Labs,
13.27 Thoughtworks Inc
13.28 MuSigma
13.29 Tableau Software LLC

14 Appendix

For more information about this report visit https://www.researchandmarkets.com/r/etjmva

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