$140+ Billion Data Science Platform Market Insights, 2020-2024 - Industry Expected to Witness a CAGR of 30%
DUBLIN, Feb. 18, 2020 /PRNewswire/ -- The "Data Science Platform Market by Component (Platform and Services), Business Function (Marketing, Sales, Logistics, and Customer Support), Deployment Mode (On-Premises and Cloud), Organization Size, Industry Vertical, and Region - Global Forecast to 2024" report has been added to ResearchAndMarkets.com's offering.
The global data science platform market is projected to grow from USD 37.9 billion in 2019 to USD 140.9 billion by 2024, at a CAGR of 30% during the forecast period.
The market's revenue is classified primarily into revenues from platform and services. Services' revenue is associated with training and consulting integration and deployment, and support and maintenance services. The market is also segmented on the basis of components, deployment modes, industry verticals, organization size, business functions, and regions.
Increasing focus of enterprises on ease of use methods for driving business to boost the data science platform market growth
Major growth factors for the market include the growing need to gain insights from voluminous data to gain a competitive advantage and enable data-driven decisions in enterprises.
Logistics industry vertical to grow at the highest CAGR during the forecast period
Based on business functions, the data science platform market is divided into Banking, Financial Services, and Insurance (BFSI), telecom and IT, retail and eCommerce, healthcare and life sciences, manufacturing, energy and utilities, media and entertainment, transportation and logistics, government, and others (travel and hospitality, education, and research).
The logistics industry vertical would benefit from the technological and methodological advancements of big data. It is changing drastically due to internal and external pressures from the rising costs. ML has the potential to revolutionize the logistics industry vertical through determining the most important factors for the success of a supply network, while it also has the potential to learn in the process. The companies such as Google and Altair have launched AI-powered solutions that make the development of ML projects easier and assist in building and running ML applications.
Cloud segment to hold a higher market share during the forecast period
Organizations have been gradually recognizing the importance of data science platform and have started deploying it as per their needs in various business functions, such as supply chain, customer support, and sales and marketing. The cloud-based data science platform is a cost-effective and efficient way of managing data science platform issues across organizations. The availability of easy deployment options and miniml requirements of capital and time are expected to facilitate the growth of the cloud segment among global enterprises.
Asia Pacific to grow at the highest CAGR during the forecast period
The growth in APAC can be attributed to the focus of countries such as China, India, and Japan on the enhanced management of data to enable data-based business decisions and enhance business processes. The commercialization of big data, AI, and IoT technologies and the need for further advancements to leverage these technologies to the best are expected to drive the adoption of data science platform and services in the region.
APAC constitutes major economies, such as China, India, and Japan, which are expected to register high growth in the data science platform market. The verticals such as healthcare and life sciences, manufacturing, and retail and eCommerce are expected to rapidly adopt data science platform and services in the region. Tremendous technological adoption over the last few decades and ongoing innovations by companies such as Cloudera, Zaloni, and Temenos have helped the market to grow significantly in the region.
Key Topics Covered
1 Introduction
2 Research Methodology
3 Executive Summary
4 Premium Insights 4.1 Attractive Opportunities in the Data Science Platform Market 4.2 Market: Top 3 Business Functions 4.3 Market: By Region 4.4 Market in North America, by Business Function and Industry Vertical
5 Market Overview and Industry Trends 5.1 Introduction 5.2 Market Dynamics 5.2.1 Drivers 5.2.1.1 Enterprises Focusing on Ease of Use Methods to Drive Business 5.2.1.2 Growing Need to Extract In-Depth Insights from Voluminous Data to Gain Competitive Advantage 5.2.2 Restraints 5.2.2.1 Stringent Government Rules and Regulations 5.2.3 Opportunities 5.2.3.1 Higher Inclination of Enterprises Toward Data-Intensive Business Strategies 5.2.3.2 Rise in Adoption of Advanced Technologies 5.2.4 Challenges 5.2.4.1 Lack of Adequately Skilled Workforce 5.2.4.2 Data Privacy, Security, and Reliability Concerns 5.3 Industry Trends 5.3.1 Value Chain Analysis 5.3.2 Use Cases 5.3.2.1 Use Case: Scenario 1 5.3.2.2 Use Case: Scenario 2 5.3.2.3 Use Case: Scenario 3 5.4 Impact of Technologies on Data Science Platform 5.4.1 Machine Learning 5.4.2 Deep Learning 5.4.3 Natural Language Processing 5.5 Regulatory Implications 5.5.1 General Data Protection Regulation 5.5.2 The International Organization for Standardization 27001 5.5.3 Payment Card Industry Data Security Standard 5.5.4 Basel Committee on Banking Supervision 239 Compliance 5.5.5 California Consumer Privacy Act 5.5.6 Health Insurance Portability and Accountability Act of 1996 5.5.7 Health Information Technology for Economic and Clinical Health Act 5.5.8 Sarbanes-Oxley Act of 2002 5.5.9 Personal Data Protection Act
6 Data Science Platform Market, By Component 6.1 Introduction 6.2 Platform 6.3 Services
7 Market, By Deployment Mode 7.1 Introduction 7.2 On-Premises 7.3 Cloud
8 Data Science Platform Market, By Organization Size 8.1 Introduction 8.2 Large Enterprises 8.3 Small and Medium-Sized Enterprises
9 Market, By Business 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 Market, By Industry Vertical 10.1 Introduction 10.2 Banking, Financial Services, and Insurance 10.3 Telecom and IT 10.4 Retail and Ecommerce 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 and Defense 10.11 Others
11 Data Science Platform Market, By Region 11.1 Introduction 11.2 North America 11.3 Europe 11.4 Asia-Pacific 11.5 Middle East and Africa 11.6 Latin America
12 Competitive Landscape 12.1 Overview 12.2 Competitive Leadership Mapping 12.2.1 Visionary Leaders 12.2.2 Innovators 12.2.3 Dynamic Differentiators 12.2.4 Emerging Companies
13 Company Profiles 13.1 Introduction 13.2 Microsoft 13.3 IBM 13.4 Google 13.5 SAS Institute 13.6 Altair 13.7 Cloudera 13.8 Alteryx 13.9 Databricks 13.10 Wolfram 13.11 MathWorks 13.12 RapidMiner 13.13 Anaconda 13.14 Bridgei2i 13.15 Rexer Analytics 13.16 Domino Data Lab 13.17 Dataiku 13.18 Civis Analytics 13.19 H2O.ai 13.20 RStudio 13.21 Rapid Insight 13.22 SAP
For more information about this report visit https://www.researchandmarkets.com/r/l38398
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