Global Data Science Platforms Market (2021-2027) – By Component, Deployment, Organization Size, Function, Industry Vertical, and Geography –

DUBLIN – (COMMERCIAL THREAD)–The “Global Data Science Platforms Market (2021-2027) by Component, Deployment, Organization Size, Function, Industry Vertical and Geography, Competitive Analysis, Impact of Covid-19, Ansoff Analysis” the report was added to offer.

The global data science platform market is estimated to be worth $ 43.3 billion in 2021 and is expected to reach $ 81.43 billion by 2027, with a CAGR of 11.1%.

Key factors such as a massive increase in the volume of data due to the increasing digitization and automation of processes have been a crucial driver of the growth of the data science platform. In addition, companies are increasingly focusing on analytical tools to gain insight into consumer behavior and purchasing patterns. This, in turn, shaped their business decisions and strategies for competing in the market. In addition, the adoption of data science platforms has made its way across various industry sectors such as manufacturing, IT, BFSI, retail, and more. All of these factors have contributed to the growth of the Data Science Platforms market.

However, the costs of deploying these platforms, as well as the shrinking workforce with domain expertise capabilities and threats to data privacy, have been a hindrance to the growth of the business. Marlet.

The global data science platform market is segmented on the basis of component, deployment, organization size, function, industry vertical, and geography.

Competitive quadrant

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

Why buy this report?

  • The report offers a comprehensive assessment of the Global Data Science Platforms Market. The report includes in-depth qualitative analysis, verifiable data from authentic sources, and market size projections. Projections are calculated using proven research methodologies.

  • The report has been compiled through extensive primary and secondary research. The main research is carried out through interviews, surveys and observations of well-known people in the industry.

  • The report includes in-depth market analysis using Porter’s 5 Force Model and Ansoff Matrix. The impact of Covid-19 on the market is also presented in the report.

  • The report also contains competitive analysis using Competitive Quadrant, Infogence’s proprietary competitive positioning tool.

Highlights of the report:

  • A comprehensive market analysis including parent industry

  • Important market dynamics and trends

  • Market segmentation

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

  • Market shares and strategies of the main players

  • Recommendations for companies to strengthen their presence in the market

Market dynamics


  • High generation of data volumes

  • Growing focus on data-driven decisions

  • Growing adoption of data science platforms across diverse verticals


  • High initial investments

  • Lack of domain expertise

  • Data privacy, security and reliability issues


  • Growing adoption of data-driven technologies by businesses

  • Growing demand for public cloud

  • Investments and financing in the development of big data and related technologies by the public and private sectors


  • Strict government rules and regulations

Companies mentioned

  • Microsoft Corporation

  • IBM Company

  • Google inc

  • Wolfram

  • DataRobot Inc.

  • Meaning of inc.

  • RapidMiner Inc.

  • Domino Data Lab

  • Dataiku SAS

  • Alteryx, Inc.

  • Oracle

  • Tibco Software Inc.

  • SAS Institute Inc.

  • SAP SE

  • Mathematical work

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