世界各国のリアルタイムなデータ・インテリジェンスで皆様をお手伝い
データサイエンスプラットフォーム市場。世界の産業動向、シェア、サイズ、成長、機会、および2021-2026年の予測Data Science Platform Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2021-2026 The global data science platform market grew at a CAGR of around 30% during 2015-2020. A data science platform is a cohesive software framework that offers fundamental building blocks to create and... もっと見る
サマリーThe global data science platform market grew at a CAGR of around 30% during 2015-2020. A data science platform is a cohesive software framework that offers fundamental building blocks to create and incorporate data science solutions into business processes, infrastructure, and products. These solutions include integrating and exploring data, and coding, building, and deploying models through applications or reports. A data science platform makes the entire dataset available in a centralized location and enables effective team collaboration and communication. Consequently, organizations from different industry verticals are nowadays deploying data science platforms to expand tool flexibility, improve data connectivity, compute resource scalability, and support a centralized business administration for core operations.One of the primary factors encouraging the adoption of data science platforms globally is the growing emphasis of companies on becoming agile and competitive in the changing marketplace dynamics. Data science platforms offer a consistent and integrated solution for building, managing and optimizing predictive models. In the healthcare sector, with the growing amount of data, from electronic medical records (EMR) and clinical databases to personal fitness trackers, medical professionals increasingly rely on these platforms to diagnose diseases faster, practice preventive medicine and explore new treatment options. Other factors influencing the market growth are the emerging trend of autonomous vehicles, the rising need to maximize logistics efficiency, and the growing entertainment industry. Apart from this, the increasing utilization of online banking services, along with the rising instances of cybersecurity, are anticipated to expand the usage of data science platforms in the banking, financial services, and insurance (BFSI) sector to detect fraudulent activities and prevent cyberattacks. Looking forward, IMARC Group expects the global data science platform market to continue its strong growth during the next five years. Key Market Segmentation: IMARC Group provides an analysis of the key trends in each sub-segment of the global data science platform market, along with forecasts at the global, regional and country level from 2021-2026. Our report has categorized the market based on region, component, application and vertical. Breakup by Component: Software Services Breakup by Application: Marketing and Sales Logistics Finance and Accounting Customer Support Others Breakup by Vertical: IT and Telecommunication Healthcare BFSI Manufacturing Retail and E-Commerce Others 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 Competitive Landscape: The competitive landscape of the industry has also been examined along with the profiles of the key players being 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. and TIBCO Software Inc. Key Questions Answered in This Report: How has the global data science platform market performed so far and how will it perform in the coming years? What has been the impact of COVID-19 on the global data science platform market? What are the key regional markets? What is the breakup of the market based on the component? What is the breakup of the market based on the application? What is the breakup of the market based on the vertical? What are the various stages in the value chain of the industry? What are the key driving factors and challenges in the industry? What is the structure of the global data science platform market and who are the key players? What is the degree of competition in the industry? 目次1 Preface2 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
SummaryThe global data science platform market grew at a CAGR of around 30% during 2015-2020. A data science platform is a cohesive software framework that offers fundamental building blocks to create and incorporate data science solutions into business processes, infrastructure, and products. These solutions include integrating and exploring data, and coding, building, and deploying models through applications or reports. A data science platform makes the entire dataset available in a centralized location and enables effective team collaboration and communication. Consequently, organizations from different industry verticals are nowadays deploying data science platforms to expand tool flexibility, improve data connectivity, compute resource scalability, and support a centralized business administration for core operations.One of the primary factors encouraging the adoption of data science platforms globally is the growing emphasis of companies on becoming agile and competitive in the changing marketplace dynamics. Data science platforms offer a consistent and integrated solution for building, managing and optimizing predictive models. In the healthcare sector, with the growing amount of data, from electronic medical records (EMR) and clinical databases to personal fitness trackers, medical professionals increasingly rely on these platforms to diagnose diseases faster, practice preventive medicine and explore new treatment options. Other factors influencing the market growth are the emerging trend of autonomous vehicles, the rising need to maximize logistics efficiency, and the growing entertainment industry. Apart from this, the increasing utilization of online banking services, along with the rising instances of cybersecurity, are anticipated to expand the usage of data science platforms in the banking, financial services, and insurance (BFSI) sector to detect fraudulent activities and prevent cyberattacks. Looking forward, IMARC Group expects the global data science platform market to continue its strong growth during the next five years. Key Market Segmentation: IMARC Group provides an analysis of the key trends in each sub-segment of the global data science platform market, along with forecasts at the global, regional and country level from 2021-2026. Our report has categorized the market based on region, component, application and vertical. Breakup by Component: Software Services Breakup by Application: Marketing and Sales Logistics Finance and Accounting Customer Support Others Breakup by Vertical: IT and Telecommunication Healthcare BFSI Manufacturing Retail and E-Commerce Others 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 Competitive Landscape: The competitive landscape of the industry has also been examined along with the profiles of the key players being 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. and TIBCO Software Inc. Key Questions Answered in This Report: How has the global data science platform market performed so far and how will it perform in the coming years? What has been the impact of COVID-19 on the global data science platform market? What are the key regional markets? What is the breakup of the market based on the component? What is the breakup of the market based on the application? What is the breakup of the market based on the vertical? What are the various stages in the value chain of the industry? What are the key driving factors and challenges in the industry? What is the structure of the global data science platform market and who are the key players? What is the degree of competition in the industry? Table of Contents1 Preface2 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
ご注文は、お電話またはWEBから承ります。お見積もりの作成もお気軽にご相談ください。本レポートと同分野（その他）の最新刊レポート
IMARC Services Private Limited. 社の最新刊レポート
本レポートと同じKEY WORD（platform）の最新刊レポート
よくあるご質問IMARC Services Private Limited.社はどのような調査会社ですか?インドに調査拠点を持つ調査会社。幅広い分野をカバーしていますがケミカルに特に焦点を当てています。 もっと見る 調査レポートの納品までの日数はどの程度ですか?在庫のあるものは速納となりますが、平均的には 3-４日と見て下さい。
注文の手続きはどのようになっていますか?1)お客様からの御問い合わせをいただきます。
お支払方法の方法はどのようになっていますか?納品と同時にデータリソース社よりお客様へ請求書（必要に応じて納品書も）を発送いたします。
データリソース社はどのような会社ですか?当社は、世界各国の主要調査会社・レポート出版社と提携し、世界各国の市場調査レポートや技術動向レポートなどを日本国内の企業・公官庁及び教育研究機関に提供しております。
|
詳細検索
2024/11/08 10:26 154.13 円 166.76 円 202.76 円 |
