데이터 사이언스 플랫폼 시장 예측(-2030년) : 도입 모드별, 컴포넌트별, 조직 규모별, 용도별, 최종사용자별, 지역별 세계 분석

According to Stratistics MRC, the Global Data Science Platform Market is accounted for $150.57 billion in 2023 and is expected to reach $746.63 billion by 2030 growing at a CAGR of 25.7% during the forecast period. Data science platform serves as a central hub for all data science and data analysis activities. The data science platform provides all the tools necessary for every stage of a project's life cycle, including ideation, setup, discovery, model development, and software implementation. Data scientists can more quickly run, track, replicate, analyze, and share their work due to the data science platform. The data science platform is one such software tool that is widely used by businesses.

According to Seagate, the storage solutions provider, the volume of data created worldwide will grow to 175 ZB by 2025.

Market Dynamics:

Driver:

Soaring use of big data

As there is growth in social media, IOT, and other media, the amount of data that professionals capture is constantly expanding. A massive flow of structured and unstructured data has been produced by data science platforms. In general, the growth of machine-based and human-generated data is 10 times greater than that of traditional corporate data, and the rate at which machine data is produced is 50 times faster. The enormous growth in data offerings provides opportunities for businesses to acquire new things, which led to a rise in demand for novel approaches and plays a critical role in driving the market for data science platforms.

Restraint:

Lack of technical proficiency

Advanced analytics techniques like streaming analytics, machine learning, and predictive analytics are frequently used in the current business environment. These techniques do, however, pose difficulties because they call for a high level of analytical proficiency. For instance, creating a machine learning model requires technical expertise, analytical prowess, and critical thinking skills. Unfortunately, many end users do not have staff members who are knowledgeable and skilled. Therefore, it is anticipated that the lack of technical know-how and trained personnel will pose a significant challenge for the market for data science platforms in the near future.

Opportunity:

High investment and technological advancements

According to estimates, the substantial investment in research and development will create profitable market opportunities and accelerate the growth of the data science platform market. Further, the market is presented with a wide range of growth opportunities due to the quick development of technologies like artificial intelligence (AI), machine learning (ML), and the internet of things (IoT).

Threat:

Uncertainty regarding the business issues

Businesses must do extensive research on the problems they want to use a data science platform to solve. Simply selecting datasets and performing data analysis can have low productivity if the business problem at hand is not understood. Making informed decisions using a data science platform is significantly less effective. A company's efforts may also be ineffective even if it has a clearly defined goal in mind if its expectations for the implementation of a data science platform do not match its goals. Throughout the anticipated period, it is anticipated that this particular factor will produce a number of growth-impeding challenges.

COVID-19 Impact:

The COVID-19 had a favorable impact on market expansion and will offer an abundance of opportunity for expansion throughout the forecast period. These opportunities include the rise in data applications, the demand for data science platforms in enterprises, and the introduction of cutting-edge data science platform solutions. Organizations were forced to move toward digitalization in order to set up work-from-home officers for their employees due to the general lockdown. As the major technology companies integrate automation and intelligence into their organizations as a result of the COVID-19 pandemic, this is driving interest in data science platforms.

The On-premises segment is expected to be the largest during the forecast period

Over the projection period, it is predicted that the on-premises segment will experience a larger market size. The practice of managing, processing, and storing data over networks of distant computers that are frequently accessed online is known as cloud computing. Businesses primarily use the data science platform's on-premises deployment strategy in highly regulated sector verticals like BFSI, healthcare and life sciences, and manufacturing. Additionally, it is anticipated that large businesses with sufficient IT resources will select the on-premises deployment approach, which is accelerating market growth.

The large enterprises segment is expected to have the highest CAGR during the forecast period

During the forecast period, it is expected that the large enterprises segment will experience lucrative growth. Large companies are generally defined as those with more than or equal to 1,000 employees. Numerous large companies are utilizing the data science platform as a result of the cloud's rising popularity, and this trend is anticipated to continue. Massive amounts of data are gathered by large companies from their diverse customer bases. In large businesses, data is essential for determining how well an organization is performing overall. The aforementioned elements are expected to cause the segment to grow.

Region with largest share:

Over the forecast period, North America is anticipated to dominate the largest market share. Key players from a variety of industries are present in this region, which is anticipated to accelerate market expansion. Additionally, rising investments in cutting-edge technologies are driving up product demand. The region's revenue share is increased by the presence of major market players there. Furthermore, the United States and Canada are consistently investing in a cutting-edge solution that can use data to aid in business decision-making. Companies in the area are utilizing technology to innovate and expand their markets.

Region with highest CAGR:

During the forecast period, a rapid growth rate is anticipated in the Asia-Pacific region. It is expected that the adoption of big data analytics tools will increase quickly across industries. In light of the numerous applications and use cases for data analytics tools, the governments of China, South Korea, India, and other countries are also making investments in these tools. Additionally, the industry in this region is also growing as a result of factors like increased spending on big data technologies in economies due to the rapid rise in the volume and complexity of numbers as a result of the increase in mobile data traffic and new IoT and AI applications in business operations, which are opening up a lot of opportunities for the market.

Key players in the market:

Some of the key players in Data Science Platform Market include: Altair Inc., Alteryx Inc., Amazon Web Services, Inc., Anaconda Inc., Apheris AI GmbH, Arrikto Inc., Cloudera Inc., Databand, Databricks, Dataiku, DataRobot Inc., Domino Data Lab Inc., Explorium Inc., Google Inc, H2O.ai, IBM Corporation, Iterative, MathWorks, Inc., Microsoft Corporation, Oracle Corporation, RapidMiner, SAP SE and Teradata.

Key Developments:

In September 2023, Anaconda is excited to announce the public release of Anaconda Assistant, an AI-powered Jupiter notebook extension designed to enhance the productivity of data scientists, developers, and researchers. Anaconda Assistant is now available to all users of Anaconda cloud notebooks. Powered by the same large language model behind ChatGPT, the Assistant provides an intuitive chat interface to help generate, explain, or debug code, learn new topics, and more.

In August 2023, Altair, a global leader in computational science and artificial intelligence (AI), announced that Lydonia Technologies, the leading provider of hyperautomation software and solutions, has joined its growing channel partner network. Lydonia Technologies will offer Altair® RapidMiner® - Altair's data analytics and AI platform - as well as Altair SLC™, an alternative SAS language environment, to customers in the U.S. Specializing in hyperautomation services and solutions, Lydonia Technologies helps companies increase the automation of their business processes through AI, machine learning, and robotic process automation (RPA).

In August 2023, Alteryx, Inc. the Analytics Cloud Platform company, is expanding its partnership with Google Cloud to provide Looker Studio users with native access to a free limited version of Alteryx Designer Cloud's AI-powered data preparation capabilities and enhanced connectivity. This new integration builds on Alteryx and Google Cloud's commitment to make it easier for customers to surface critical insights for decision-makers in a timely manner, resulting in actions that can improve business outcomes.

Deployment Modes Covered:

• Cloud
• On-premises

Components Covered:

• Consulting
• Deployment and Integration
• Platform
• Support and Maintenance
• Services

Organization Sizes Covered:

• Small and Medium-Sized Enterprises
• Large Enterprises

Applications Covered:

• Customer Support
• Finance and Accounting
• Human Resources and Operations
• Logistics
• Marketing
• Sales
• Other Applications

End Users Covered:

• Banking, Financial Services and Insurance (BFSI)
• Energy and Utilities
• Government and Defense
• Healthcare and Life Sciences
• Information Technology and Telecommunication
• Manufacturing
• Media and Entertainment
• Retail and e-Commerce
• Transportation and Logistics
• Other End Users

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • Rest of Middle East & Africa

What our report offers:

• Market share assessments for the regional and country-level segments
• Strategic recommendations for the new entrants
• Covers Market data for the years 2021, 2022, 2023, 2026, and 2030
• Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
• Strategic recommendations in key business segments based on the market estimations
• Competitive landscaping mapping the key common trends
• Company profiling with detailed strategies, financials, and recent developments
• Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

• Company Profiling
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
  • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

• 2.1 Abstract
• 2.2 Stake Holders
• 2.3 Research Scope
• 2.4 Research Methodology
  • 2.4.1 Data Mining
  • 2.4.2 Data Analysis
  • 2.4.3 Data Validation
  • 2.4.4 Research Approach
• 2.5 Research Sources
  • 2.5.1 Primary Research Sources
  • 2.5.2 Secondary Research Sources
  • 2.5.3 Assumptions

3 Market Trend Analysis

• 3.1 Introduction
• 3.2 Drivers
• 3.3 Restraints
• 3.4 Opportunities
• 3.5 Threats
• 3.6 Application Analysis
• 3.7 End User Analysis
• 3.8 Impact of Covid-19

4 Porters Five Force Analysis

• 4.1 Bargaining power of suppliers
• 4.2 Bargaining power of buyers
• 4.3 Threat of substitutes
• 4.4 Threat of new entrants
• 4.5 Competitive rivalry

5 Global Data Science Platform Market, By Deployment Mode

• 5.1 Introduction
• 5.2 Cloud
• 5.3 On-premises

6 Global Data Science Platform Market, By Component

• 6.1 Introduction
• 6.2 Consulting
• 6.3 Deployment and Integration
• 6.4 Platform
• 6.5 Support and Maintenance
• 6.6 Services
  • 6.6.1 Professional Services
  • 6.6.2 Managed Services

7 Global Data Science Platform Market, By Organization Size

• 7.1 Introduction
• 7.2 Small and Medium-Sized Enterprises
• 7.3 Large Enterprises

8 Global Data Science Platform Market, By Application

• 8.1 Introduction
• 8.2 Customer Support
• 8.3 Finance and Accounting
• 8.4 Human Resources and Operations
• 8.5 Logistics
• 8.6 Marketing
• 8.7 Sales
• 8.8 Other Applications

9 Global Data Science Platform Market, By End User

• 9.1 Introduction
• 9.2 Banking, Financial Services and Insurance (BFSI)
• 9.3 Energy and Utilities
• 9.4 Government and Defense
• 9.5 Healthcare and Life Sciences
• 9.6 Information Technology and Telecommunication
• 9.7 Manufacturing
• 9.8 Media and Entertainment
• 9.9 Retail and e-Commerce
• 9.10 Transportation and Logistics
• 9.11 Other End Users

10 Global Data Science Platform Market, By Geography

• 10.1 Introduction
• 10.2 North America
  • 10.2.1 US
  • 10.2.2 Canada
  • 10.2.3 Mexico
• 10.3 Europe
  • 10.3.1 Germany
  • 10.3.2 UK
  • 10.3.3 Italy
  • 10.3.4 France
  • 10.3.5 Spain
  • 10.3.6 Rest of Europe
• 10.4 Asia Pacific
  • 10.4.1 Japan
  • 10.4.2 China
  • 10.4.3 India
  • 10.4.4 Australia
  • 10.4.5 New Zealand
  • 10.4.6 South Korea
  • 10.4.7 Rest of Asia Pacific
• 10.5 South America
  • 10.5.1 Argentina
  • 10.5.2 Brazil
  • 10.5.3 Chile
  • 10.5.4 Rest of South America
• 10.6 Middle East & Africa
  • 10.6.1 Saudi Arabia
  • 10.6.2 UAE
  • 10.6.3 Qatar
  • 10.6.4 South Africa
  • 10.6.5 Rest of Middle East & Africa

11 Key Developments

• 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 11.2 Acquisitions & Mergers
• 11.3 New Product Launch
• 11.4 Expansions
• 11.5 Other Key Strategies

12 Company Profiling

• 12.1 Altair Inc.
• 12.2 Alteryx Inc.
• 12.3 Amazon Web Services, Inc.
• 12.4 Anaconda Inc.
• 12.5 Apheris AI GmbH
• 12.6 Arrikto Inc.
• 12.7 Cloudera Inc.
• 12.8 Databand
• 12.9 Databricks
• 12.10 Dataiku
• 12.11 DataRobot Inc.
• 12.12 Domino Data Lab Inc.
• 12.13 Explorium Inc.
• 12.14 Google Inc
• 12.15 H2O.ai
• 12.16 IBM Corporation
• 12.17 Iterative
• 12.18 MathWorks, Inc.
• 12.19 Microsoft Corporation
• 12.20 Oracle Corporation
• 12.21 RapidMiner
• 12.22 SAP SE
• 12.23 Teradata