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1541324

2024-2032 年按組件、應用、垂直產業和地區分類的數據科學平台市場報告

Data Science Platform Market Report by Component, Application, Vertical, and Region 2024-2032

出版日期: | 出版商: IMARC | 英文 144 Pages | 商品交期: 2-3個工作天內

價格

2023 年,全球資料科學IMARC Group市場規模達到 118 億美元。醫療保健產業中資料科學平台的利用率不斷上升,各種商業組織對基於雲端的程式的需求不斷成長,以及資料科學平台中先進技術的不斷整合是推動市場的一些關鍵因素。

資料科學平台是一個綜合性的軟體和硬體基礎設施,提供資料科學過程各個方面所需的工具、技術和資源。數據科學是一個多學科領域,涉及收集、清理、分析和解釋資料,以提取有價值的見解並做出數據驅動的決策。這些平台包括資料提取、轉換和載入 (ETL) 工具,以及資料庫、資料倉儲、API 和其他資料來源的連接器。他們還提供廣泛的機器學習演算法和建模工​​具,用於建立預測和描述模型。

目前,由於數據科學平台能夠有效分析、監督和整合大量結構化和非結構化資料,醫療保健產業擴大採用資料科學平台,這主要推動了市場的成長。此外,全球不同商業實體對基於雲端的解決方案的日益偏好正在培育有利的市場格局。此外,全球範圍內對具有成本效益、高效且增強的決策工具的需求不斷成長。需求的激增,加上資料科學平台利用率的不斷擴大,增強了企業分析和生產力,正在推動市場成長。此外,人工智慧 (AI)、物聯網 (IoT) 和機器學習 (ML) 與資料科學平台的整合為行業利益相關者帶來了利潤豐厚的成長機會。此外,人們對資料科學平台的需求日益成長,這些平台提供了一種一致且整合的方法來建立、管理和最佳化企業預測模型,正在對市場產生積極影響。此外,在巨量資料技術發展的推動下,對資料科學平台的需求不斷成長,也促進了市場的擴張。此外,由於銀行服務利用率的不斷提高,BFSI 領域對資料科學平台的需求不斷增加,這進一步加強了市場的成長。

數據科學平台市場趨勢/促進因素:

醫療保健產業資料科學平台的使用率不斷提高

醫療保健會產生大量資料,包括結構化數據(患者記錄)和非結構化數據,例如醫學影像和臨床記錄。數據科學平台使醫療保健提供者能夠有效地分析、管理和吸收這些豐富的資訊。例如,他們可以使用資料分析來識別患者群體的趨勢、模式和潛在的健康風險。此外,這些平台使醫療保健專業人員能夠利用預測分析。他們可以預測疾病爆發,識別可能需要更多關注的高風險患者,甚至預測患者的治療結果。這種預測能力增強了病患照護和資源分配。此外,在製藥和生物技術領域,資料科學平台在藥物發現和開發方面發揮重要作用。研究人員可以分析遺傳資料、臨床試驗結果和藥物交互作用,以加快將新療法推向市場的進程。

各種商業組織對基於雲端的程式的需求不斷成長

基於雲端的平台提供可擴展性來處理大型資料集和運算需求。企業可以根據需要擴大或縮小其資源,從而提供管理資料科學專案的靈活性。此外,這些解決方案通常需要較低的硬體和基礎設施前期投資。這種成本效益吸引了各種規模的組織,尤其是新創公司和小型企業。此外,基於雲端的平台支援遠端訪問,促進地理位置分散的團隊之間的協作。這種可訪問性在當今全球化的商業環境中至關重要。此外,雲端供應商負責軟體更新和基礎設施維護,減輕內部 IT 團隊的負擔,並確保組織始終能夠存取最新的功能和安全性修補程式。

資料科學平台中先進技術的不斷整合

人工智慧和機器學習演算法正在成為資料科學平台不可或缺的一部分。它們支援自動化、預測建模、自然語言處理和異常檢測。這些高級功能對於從複雜的資料集中提取有價值的見解至關重要。此外,隨著物聯網設備在各行業的激增,資料科學平台正在適應處理這些設備產生的大量資料。他們可以分析來自感測器、設備和機器的資料,以提供即時見解並改善決策。此外,先進的技術使資料科學平台能夠提供更複雜的資料視覺化技術。這增強了向利害關係人有效傳達見解的能力。

目錄

第1章:前言

第 2 章:範圍與方法

  • 研究目的
  • 利害關係人
  • 數據來源
    • 主要來源
    • 二手資料
  • 市場預測
    • 自下而上的方法
    • 自上而下的方法
  • 預測方法

第 3 章:執行摘要

第 4 章:簡介

  • 概述
  • 主要行業趨勢

第 5 章:全球資料科學平台市場

  • 市場概況
  • 市場表現
  • COVID-19 的影響
  • 市場預測

第 6 章:市場區隔:按組成部分

  • 軟體
    • 市場趨勢
    • 市場預測
  • 服務
    • 市場趨勢
    • 市場預測

第 7 章:市場區隔:按應用

  • 行銷與銷售
    • 市場趨勢
    • 市場預測
  • 後勤
    • 市場趨勢
    • 市場預測
  • 財會
    • 市場趨勢
    • 市場預測
  • 客戶支援
    • 市場趨勢
    • 市場預測
  • 其他
    • 市場趨勢
    • 市場預測

第 8 章:市場區隔:依垂直領域

  • 資訊科技和電信
    • 市場趨勢
    • 市場預測
  • 衛生保健
    • 市場趨勢
    • 市場預測
  • BFSI
    • 市場趨勢
    • 市場預測
  • 製造業
    • 市場趨勢
    • 市場預測
  • 零售與電子商務
    • 市場趨勢
    • 市場預測
  • 其他
    • 市場趨勢
    • 市場預測

第 9 章:市場區隔:按地區

  • 北美洲
    • 美國
    • 加拿大
  • 亞太
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 其他
  • 歐洲
    • 德國
    • 法國
    • 英國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 其他
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 其他
  • 中東和非洲
    • 市場趨勢
    • 市場細分:按國家/地區
    • 市場預測

第 10 章:SWOT 分析

  • 概述
  • 優勢
  • 弱點
  • 機會
  • 威脅

第 11 章:價值鏈分析

第 12 章:波特五力分析

  • 概述
  • 買家的議價能力
  • 供應商的議價能力
  • 競爭程度
  • 新進入者的威脅
  • 替代品的威脅

第 13 章:價格分析

第14章:競爭格局

  • 市場結構
  • 關鍵參與者
  • 關鍵參與者簡介
    • Alteryx Inc.
    • Cloudera Inc.
    • Dataiku Inc.
    • Google LLC (Alphabet Inc.)
    • H2O.ai Inc.
    • International Business Machines Corporation
    • Microsoft Corporation
    • RapidMiner Inc.
    • SAP SE
    • SAS Institute Inc.
    • The MathWorks Inc.
    • TIBCO Software Inc.
Product Code: SR112024A3601

The global data science platform market size reached US$ 11.8 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 119.9 Billion by 2032, exhibiting a growth rate (CAGR) of 28.5% during 2024-2032. The rising utilization of data science platforms in the healthcare industry, the growing demand for cloud-based programs in various business organizations, and the rising integration of advanced technologies in data science platforms represent some of the key factors driving the market.

A data science platform is a comprehensive software and hardware infrastructure that provides the tools, technologies, and resources necessary for various aspects of the data science process. Data science is a multidisciplinary field that involves collecting, cleaning, analyzing, and interpreting data to extract valuable insights and make data-driven decisions. These platforms include tools for data extraction, transformation, and loading (ETL), as well as connectors to databases, data warehouses, APIs, and other data sources. They also offer a wide range of machine learning algorithms and modeling tools for building predictive and descriptive models.

Currently, the increased adoption of data science platforms within the healthcare sector, owing to their ability to efficiently analyze, oversee, and integrate vast volumes of structured and unstructured data is primarily driving the market growth. Furthermore, the increasing preference for cloud-based solutions across diverse global business entities is fostering a favorable market landscape. Additionally, there is a growing demand for cost-effective, efficient, and enhanced decision-making tools on a global scale. This surge in demand, coupled with the expanding utilization of data science platforms, which enhance enterprise analysis and productivity, is propelling market growth. Moreover, the integration of artificial intelligence (AI), the internet of things (IoT), and machine learning (ML) into data science platforms is presenting lucrative growth opportunities for industry stakeholders. Furthermore, the increasing appetite for data science platforms, which offer a cohesive and integrated approach to constructing, managing, and optimizing predictive models for businesses, is exerting a positive influence on the market. Additionally, the escalating demand for data science platforms, driven by the evolution of big data technologies, is contributing to market expansion. Furthermore, the heightened need for data science platforms within the BFSI sector due to the growing utilization of banking services is further strengthening the market growth.

Data Science Platform Market Trends/Drivers:

Rising utilization of data science platforms in the healthcare industry

Healthcare generates an enormous amount of data, both structured (patient records) and unstructured such as medical images and clinical notes. Data science platforms enable healthcare providers to effectively analyze, manage, and assimilate this wealth of information. For instance, they can use data analytics to identify trends, patterns, and potential health risks among patient populations. Besides, these platforms empower healthcare professionals to leverage predictive analytics. They can forecast disease outbreaks, identify high-risk patients who may require more attention, and even predict patient outcomes. This predictive capability enhances patient care and resource allocation. Moreover, in the pharmaceutical and biotechnology sectors, data science platforms are instrumental in drug discovery and development. Researchers can analyze genetic data, clinical trial results, and drug interactions to accelerate the process of bringing new treatments to market.

Growing demand for cloud-based programs in various business organizations

Cloud-based platforms offer scalability to handle large datasets and computational demands. Businesses can scale their resources up or down as needed, providing flexibility in managing their data science projects. Besides, these solutions often require lower upfront investment in hardware and infrastructure. This cost-effectiveness appeals to organizations of all sizes, especially startups and small businesses. Moreover, cloud-based platforms enable remote access, facilitating collaboration among geographically dispersed teams. This accessibility is crucial in today's globalized business environment. Additionally, cloud providers handle software updates and infrastructure maintenance, reducing the burden on in-house IT teams and ensuring that organizations always have access to the latest features and security patches.

Rising integration of advanced technologies in data science platforms

AI and ML algorithms are becoming integral parts of data science platforms. They enable automation, predictive modeling, natural language processing, and anomaly detection. These advanced capabilities are essential for extracting valuable insights from complex datasets. Moreover, with the proliferation of IoT devices in various industries, data science platforms are adapting to handle the massive influx of data generated by these devices. They can analyze data from sensors, devices, and machines to provide real-time insights and improve decision-making. Besides, advanced technologies enable data science platforms to offer more sophisticated data visualization techniques. This enhances the ability to convey insights to stakeholders effectively.

Data Science Platform Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the global, regional and country levels from 2024-2032. Our report has categorized the market based on component, application and vertical.

Breakup by Component:

Software

Services

Software represents the most popular component

The report has provided a detailed breakup and analysis of the market based on the component. This includes software and services. According to the report, software represented the largest segment.

Data science software offers a wide range of tools and capabilities for data collection, cleaning, analysis, modeling, and visualization. It provides data scientists with the flexibility to perform a multitude of tasks within a single platform. Moreover, it is readily available and accessible to organizations of all sizes. Many software solutions are user-friendly, making them accessible to both data science experts and those with less technical expertise. Besides, software solutions can be scaled up or down to accommodate different data volumes and complexities. This scalability is crucial in handling the ever-increasing amount of data generated by organizations.

Breakup by Application:

Marketing and Sales

Logistics

Finance and Accounting

Customer Support

Others

Marketing and sales hold the largest market share

A detailed breakup and analysis of the market based on the application has also been provided in the report. This includes marketing and sales, logistics, finance and accounting, customer support, and others. According to the report, marketing and sales represented the largest segment.

Marketing and sales are inherently data-intensive fields. They heavily rely on data to make informed decisions about product development, pricing strategies, customer segmentation, and sales forecasting. Data science platforms provide the tools and capabilities to process and analyze vast datasets, enabling more accurate and data-driven decision-making. Besides, understanding customer behavior, preferences, and needs is critical for effective marketing and sales strategies. Data science platforms help organizations gather, analyze, and extract actionable insights from customer data. This allows businesses to tailor their marketing campaigns and sales efforts to target specific customer segments more effectively. Moreover, these platforms assist in optimizing marketing campaigns by analyzing campaign performance metrics and identifying which strategies are most effective. This allows marketers to allocate resources to the most successful campaigns and refine their approaches in real-time.

Breakup by Vertical:

IT and Telecommunication

Healthcare

BFSI

Manufacturing

Retail and E-Commerce

Others

BFSI accounts for the majority of market share

A detailed breakup and analysis of the market based on the vertical has also been provided in the report. This includes IT and telecommunication, healthcare, BFSI, manufacturing, retail and e-commerce, and others. According to the report, BFSI represented the largest segment.

The BFSI industry deals with vast volumes of data, including customer transactions, financial records, market data, and risk assessments. Data science platforms are essential for processing and analyzing this extensive data to extract valuable insights, detect fraudulent activities, and make informed decisions. Besides, risk assessment is a critical aspect of the BFSI sector. Data science platforms equipped with machine learning and predictive analytics help banks and financial institutions assess and mitigate risks effectively. These platforms can identify potential credit defaults, market fluctuations, and fraudulent transactions, which is crucial for maintaining financial stability.

Breakup by Region:

North America

United States

Canada

Asia-Pacific

China

Japan

India

South Korea

Australia

Indonesia

Others

Europe

Germany

France

United Kingdom

Italy

Spain

Russia

Others

Latin America

Brazil

Mexico

Others

Middle East and Africa

North America leads the market, accounting for the majority of the data science platform market share

The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America was the largest market.

North America, particularly the United States, is home to many technology hubs such as Silicon Valley, which is known for innovation and technological advancements. This region fosters a fertile ground for the development and adoption of cutting-edge data science technologies and platforms. Moreover, the region hosts a vast number of large enterprises, including Fortune 500 companies, across various industries. These enterprises have substantial budgets and resources to invest in data science platforms to gain a competitive edge, improve operational efficiency, and drive innovation. Besides, North America leads in research and development activities related to data science and artificial intelligence (AI). Leading universities, research institutions, and tech companies in the region continually push the boundaries of data science capabilities, leading to the development of state-of-the-art platforms and tools.

Competitive Landscape:

The competitive landscape of the market is characterized by the presence of multiple players that include established brands, emerging startups, and specialty manufacturers. Presently, leading companies are investing in research and development to enhance their data science platforms. They are introducing new features, tools, and capabilities to stay ahead of evolving industry trends and customer demands. This includes the integration of artificial intelligence (AI), machine learning (ML), and automation to improve data analytics and predictive modeling. Besides, many key players are expanding their cloud-based data science platform offerings. Cloud platforms provide scalability, flexibility, and accessibility, which are highly valued by businesses. This expansion enables organizations to harness the power of data science without significant infrastructure investments. Moreover, they are acquiring innovative startups and smaller companies in the data science and analytics space. These acquisitions enable them to quickly gain access to cutting-edge technologies, talent, and customer bases.

The market research report has provided a comprehensive analysis of the competitive landscape. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

Alteryx Inc.

Cloudera Inc.

Dataiku Inc.

Google LLC (Alphabet Inc.)

H2O.ai Inc.

International Business Machines Corporation

Microsoft Corporation

RapidMiner Inc.

SAP SE

SAS Institute Inc.

The MathWorks Inc.

TIBCO Software Inc.

(Please note that this is only a partial list of the key players, and the complete list is provided in the report.)

Recent Developments:

In November 2022, Alteryx Inc., launched innovations in analytics and data science automation, analytics in the cloud, machine learning (ML), and artificial intelligence (AI) during the company's Virtual Global Inspire conference. The new designer interface will be powered by the Alteryx Analytics Cloud platform, providing all cloud users access to the browser-based no-code analytics tool, with in-database pushdown processing for cloud data warehouses.

In September 2021, Microsoft updates Microsoft Machine Learning Studio which adds a new PyTorch extension library for agile deep learning experimentation.

In September 2021, MathWorks updated The MATLAB and Simulink product families. They included new and updated features and functions major improvements, code refactoring and block editing, and the ability to run Python commands and scripts from MATLAB.

Key Questions Answered in This Report

  • 1. How big is the global data science platform market?
  • 2. What is the expected growth rate of the global data science platform market during 2024-2032?
  • 3. What are the key factors driving the global data science platform market?
  • 4. What has been the impact of COVID-19 on the global data science platform market?
  • 5. What is the breakup of the global data science platform market based on the component?
  • 6. What is the breakup of the global data science platform market based on the application?
  • 7. What is the breakup of the global data science platform market based on the vertical?
  • 8. What are the key regions in the global data science platform market?
  • 9. Who are the key players/companies in the global data science platform market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

  • 4.1 Overview
  • 4.2 Key Industry Trends

5 Global Data Science Platform Market

  • 5.1 Market Overview
  • 5.2 Market Performance
  • 5.3 Impact of COVID-19
  • 5.4 Market Forecast

6 Market Breakup by Component

  • 6.1 Software
    • 6.1.1 Market Trends
    • 6.1.2 Market Forecast
  • 6.2 Services
    • 6.2.1 Market Trends
    • 6.2.2 Market Forecast

7 Market Breakup by Application

  • 7.1 Marketing and Sales
    • 7.1.1 Market Trends
    • 7.1.2 Market Forecast
  • 7.2 Logistics
    • 7.2.1 Market Trends
    • 7.2.2 Market Forecast
  • 7.3 Finance and Accounting
    • 7.3.1 Market Trends
    • 7.3.2 Market Forecast
  • 7.4 Customer Support
    • 7.4.1 Market Trends
    • 7.4.2 Market Forecast
  • 7.5 Others
    • 7.5.1 Market Trends
    • 7.5.2 Market Forecast

8 Market Breakup by Vertical

  • 8.1 IT and Telecommunication
    • 8.1.1 Market Trends
    • 8.1.2 Market Forecast
  • 8.2 Healthcare
    • 8.2.1 Market Trends
    • 8.2.2 Market Forecast
  • 8.3 BFSI
    • 8.3.1 Market Trends
    • 8.3.2 Market Forecast
  • 8.4 Manufacturing
    • 8.4.1 Market Trends
    • 8.4.2 Market Forecast
  • 8.5 Retail and E-Commerce
    • 8.5.1 Market Trends
    • 8.5.2 Market Forecast
  • 8.6 Others
    • 8.6.1 Market Trends
    • 8.6.2 Market Forecast

9 Market Breakup by Region

  • 9.1 North America
    • 9.1.1 United States
      • 9.1.1.1 Market Trends
      • 9.1.1.2 Market Forecast
    • 9.1.2 Canada
      • 9.1.2.1 Market Trends
      • 9.1.2.2 Market Forecast
  • 9.2 Asia-Pacific
    • 9.2.1 China
      • 9.2.1.1 Market Trends
      • 9.2.1.2 Market Forecast
    • 9.2.2 Japan
      • 9.2.2.1 Market Trends
      • 9.2.2.2 Market Forecast
    • 9.2.3 India
      • 9.2.3.1 Market Trends
      • 9.2.3.2 Market Forecast
    • 9.2.4 South Korea
      • 9.2.4.1 Market Trends
      • 9.2.4.2 Market Forecast
    • 9.2.5 Australia
      • 9.2.5.1 Market Trends
      • 9.2.5.2 Market Forecast
    • 9.2.6 Indonesia
      • 9.2.6.1 Market Trends
      • 9.2.6.2 Market Forecast
    • 9.2.7 Others
      • 9.2.7.1 Market Trends
      • 9.2.7.2 Market Forecast
  • 9.3 Europe
    • 9.3.1 Germany
      • 9.3.1.1 Market Trends
      • 9.3.1.2 Market Forecast
    • 9.3.2 France
      • 9.3.2.1 Market Trends
      • 9.3.2.2 Market Forecast
    • 9.3.3 United Kingdom
      • 9.3.3.1 Market Trends
      • 9.3.3.2 Market Forecast
    • 9.3.4 Italy
      • 9.3.4.1 Market Trends
      • 9.3.4.2 Market Forecast
    • 9.3.5 Spain
      • 9.3.5.1 Market Trends
      • 9.3.5.2 Market Forecast
    • 9.3.6 Russia
      • 9.3.6.1 Market Trends
      • 9.3.6.2 Market Forecast
    • 9.3.7 Others
      • 9.3.7.1 Market Trends
      • 9.3.7.2 Market Forecast
  • 9.4 Latin America
    • 9.4.1 Brazil
      • 9.4.1.1 Market Trends
      • 9.4.1.2 Market Forecast
    • 9.4.2 Mexico
      • 9.4.2.1 Market Trends
      • 9.4.2.2 Market Forecast
    • 9.4.3 Others
      • 9.4.3.1 Market Trends
      • 9.4.3.2 Market Forecast
  • 9.5 Middle East and Africa
    • 9.5.1 Market Trends
    • 9.5.2 Market Breakup by Country
    • 9.5.3 Market Forecast

10 SWOT Analysis

  • 10.1 Overview
  • 10.2 Strengths
  • 10.3 Weaknesses
  • 10.4 Opportunities
  • 10.5 Threats

11 Value Chain Analysis

12 Porters Five Forces Analysis

  • 12.1 Overview
  • 12.2 Bargaining Power of Buyers
  • 12.3 Bargaining Power of Suppliers
  • 12.4 Degree of Competition
  • 12.5 Threat of New Entrants
  • 12.6 Threat of Substitutes

13 Price Analysis

14 Competitive Landscape

  • 14.1 Market Structure
  • 14.2 Key Players
  • 14.3 Profiles of Key Players
    • 14.3.1 Alteryx Inc.
      • 14.3.1.1 Company Overview
      • 14.3.1.2 Product Portfolio
      • 14.3.1.3 Financials
    • 14.3.2 Cloudera Inc.
      • 14.3.2.1 Company Overview
      • 14.3.2.2 Product Portfolio
      • 14.3.2.3 Financials
    • 14.3.3 Dataiku Inc.
      • 14.3.3.1 Company Overview
      • 14.3.3.2 Product Portfolio
    • 14.3.4 Google LLC (Alphabet Inc.)
      • 14.3.4.1 Company Overview
      • 14.3.4.2 Product Portfolio
      • 14.3.4.3 SWOT Analysis
    • 14.3.5 H2O.ai Inc.
      • 14.3.5.1 Company Overview
      • 14.3.5.2 Product Portfolio
    • 14.3.6 International Business Machines Corporation
      • 14.3.6.1 Company Overview
      • 14.3.6.2 Product Portfolio
      • 14.3.6.3 Financials
      • 14.3.6.4 SWOT Analysis
    • 14.3.7 Microsoft Corporation
      • 14.3.7.1 Company Overview
      • 14.3.7.2 Product Portfolio
      • 14.3.7.3 Financials
      • 14.3.7.4 SWOT Analysis
    • 14.3.8 RapidMiner Inc.
      • 14.3.8.1 Company Overview
      • 14.3.8.2 Product Portfolio
    • 14.3.9 SAP SE
      • 14.3.9.1 Company Overview
      • 14.3.9.2 Product Portfolio
      • 14.3.9.3 Financials
      • 14.3.9.4 SWOT Analysis
    • 14.3.10 SAS Institute Inc.
      • 14.3.10.1 Company Overview
      • 14.3.10.2 Product Portfolio
      • 14.3.10.3 SWOT Analysis
    • 14.3.11 The MathWorks Inc.
      • 14.3.11.1 Company Overview
      • 14.3.11.2 Product Portfolio
    • 14.3.12 TIBCO Software Inc.
      • 14.3.12.1 Company Overview
      • 14.3.12.2 Product Portfolio
      • 14.3.12.3 SWOT Analysis

List of Figures

  • Figure 1: Global: Data Science Platform Market: Major Drivers and Challenges
  • Figure 2: Global: Data Science Platform Market: Sales Value (in Billion US$), 2018-2023
  • Figure 3: Global: Data Science Platform Market Forecast: Sales Value (in Billion US$), 2024-2032
  • Figure 4: Global: Data Science Platform Market: Breakup by Component (in %), 2023
  • Figure 5: Global: Data Science Platform Market: Breakup by Application (in %), 2023
  • Figure 6: Global: Data Science Platform Market: Breakup by Vertical (in %), 2023
  • Figure 7: Global: Data Science Platform Market: Breakup by Region (in %), 2023
  • Figure 8: Global: Data Science Platform (Software) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 9: Global: Data Science Platform (Software) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 10: Global: Data Science Platform (Services) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 11: Global: Data Science Platform (Services) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 12: Global: Data Science Platform (Marketing and Sales) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 13: Global: Data Science Platform (Marketing and Sales) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 14: Global: Data Science Platform (Logistics) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 15: Global: Data Science Platform (Logistics) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 16: Global: Data Science Platform (Finance and Accounting) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 17: Global: Data Science Platform (Finance and Accounting) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 18: Global: Data Science Platform (Customer Support) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 19: Global: Data Science Platform (Customer Support) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 20: Global: Data Science Platform (Other Applications) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 21: Global: Data Science Platform (Other Applications) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 22: Global: Data Science Platform (IT and Telecommunication) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 23: Global: Data Science Platform (IT and Telecommunication) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 24: Global: Data Science Platform (Healthcare) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 25: Global: Data Science Platform (Healthcare) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 26: Global: Data Science Platform (BFSI) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 27: Global: Data Science Platform (BFSI) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 28: Global: Data Science Platform (Manufacturing) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 29: Global: Data Science Platform (Manufacturing) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 30: Global: Data Science Platform (Retail and E-commerce) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 31: Global: Data Science Platform (Retail and E-commerce) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 32: Global: Data Science Platform (Other Verticals) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 33: Global: Data Science Platform (Other Verticals) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 34: North America: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 35: North America: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 36: United States: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 37: United States: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 38: Canada: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 39: Canada: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 40: Asia-Pacific: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 41: Asia-Pacific: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 42: China: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 43: China: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 44: Japan: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 45: Japan: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 46: India: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 47: India: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 48: South Korea: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 49: South Korea: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 50: Australia: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 51: Australia: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 52: Indonesia: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 53: Indonesia: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 54: Others: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 55: Others: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 56: Europe: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 57: Europe: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 58: Germany: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 59: Germany: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 60: France: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 61: France: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 62: United Kingdom: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 63: United Kingdom: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 64: Italy: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 65: Italy: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 66: Spain: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 67: Spain: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 68: Russia: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 69: Russia: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 70: Others: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 71: Others: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 72: Latin America: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 73: Latin America: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 74: Brazil: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 75: Brazil: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 76: Mexico: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 77: Mexico: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 78: Others: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 79: Others: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 80: Middle East and Africa: Data Science Platform Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 81: Middle East and Africa: Data Science Platform Market: Breakup by Country (in %), 2023
  • Figure 82: Middle East and Africa: Data Science Platform Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 83: Global: Data Science Platform Industry: SWOT Analysis
  • Figure 84: Global: Data Science Platform Industry: Value Chain Analysis
  • Figure 85: Global: Data Science Platform Industry: Porter's Five Forces Analysis

List of Tables

  • Table 1: Global: Data Science Platform Market: Key Industry Highlights, 2023 and 2032
  • Table 2: Global: Data Science Platform Market Forecast: Breakup by Component (in Million US$), 2024-2032
  • Table 3: Global: Data Science Platform Market Forecast: Breakup by Application (in Million US$), 2024-2032
  • Table 4: Global: Data Science Platform Market Forecast: Breakup by Vertical (in Million US$), 2024-2032
  • Table 5: Global: Data Science Platform Market Forecast: Breakup by Region (in Million US$), 2024-2032
  • Table 6: Global: Data Science Platform Market: Competitive Structure
  • Table 7: Global: Data Science Platform Market: Key Players