Analysis of the Data Science Platform Market: Assessment of Market Size, Trends, Statistics, and Competitors
Global Data Science Platform Market by Component (Platform, Services, Support & Maintenance, and Deployment & Integration), by Deployment (On-Premise, Cloud, and Hybrid), by Enterprise Size (SMEs & Large), by End User (IT & Telecommunication, Healthcare, BSFI, Manufacturing, Retail, and Others), by Application (Marketing & Sales, Logistics, Financing & Accounting, and Others), and by Region (North America, Europe, Asia Pacific, Latin America, and the Middle East & Africa) – Market Size, Share, COVID-19 Impact, Regional Analysis & Forecast Till 2030
Category - ICT
Report Code - OMR-ICT-180
Format: PDF, PPT, and Excel
Data Science Platform Market Overview
Data science platforms are software that provides access to many tools for advanced analytics and machine learning. It provides a unified platform where data scientists can collaborate on strategic planning, data discovery, and the dissemination of insights across an organization. Several programs, each tailored to a certain part of the data modeling procedure, are typically used in data science projects. Rapid technological progress can be attributed to the increased funding for R&D. The need for tools that help boost business output is rising as companies expand their operations. The number of organizations using platforms for data analysis is growing significantly. The software's scalability and adaptability to open-source tools are particularly noteworthy. It's also flexible enough to fit into any number of data architectures. Additionally, version control is supported on the platform, allowing the data science team to work together on projects without fear of losing any of the most recent results of their labor. These advantages are a major reason why the market is expanding so rapidly. Machine learning, streaming analytics, and forecasting are examples of advanced analytics businesses use. Technical knowledge and analytical ability in machine learning model development require certain skills. Some of the market's end-users don't have enough workers with the right skills and expertise to fuel expansion. The pandemic has stimulated market development and is expected to provide many expansion possibilities throughout the forecast.
Data Science Platform Market Growth Factors
Integration of Platform Within Crucial Sectors Such as Healthcare to Promote Increased Demand
This software aids in analyzing, managing, and integrating healthcare systems' massive volumes of organized, fragmented, and unstructured data. Patient-level evaluated historical data from industrial and academic phase III clinical trials are integrated, shared, and evaluated for the benefit of many medical research groups. Data science includes collecting and analyzing such comprehensive data sets, which is useful in pharmaceutical R&D. In addition, these cloud-based systems may be hosted on Azure, GCP, AWS, or a private cloud as a single-tenant platform. The utilization of data science platforms is on the rise right now. The initiative provides open-source software with extensive computational resource scalability and adaptability. Furthermore, it is easy to conform to various data structures. The version control features of the platform also make it possible for the statistical science team to work together without fear of losing any of their recent progress. These benefits greatly aid the growth of the market. Businesses are rethinking their starting assumptions from their data analysis. New cyclical patterns are emerging. Trends in the current market include data replacement, transportation shifts, and a spotlight on healthcare supply chains. The healthcare sector has suffered the greatest losses due to the pandemic. Experts in the medical field are focusing on leveraging data from countries hit by the pandemic in the past to get more detailed findings. This system incorporates a wide range of machine learning and analytics tools. This facilitates collaboration among data scientists working independently on a project by allowing them to independently develop methodologies, draw conclusions on data, and discuss their findings. Data science projects use specialized tools developed for usage at various points during data modeling.
Accelerating Growth of Big Data to Extract Maximum Revenue from Market
Data governance and supplying the necessary infrastructure and tools fall under the purview of IT administrators who assist a big team of data analysts in an enterprise context. Possibilities and difficulties arise from the abundance of data mining tools and applications. In 2020, IBM predicted that the demand for data scientists would increase by 28%. Big data use is rising as more and more businesses use massive volumes of organized and unstructured data. For example, by 2020, the world's data volume is projected to reach 47 zettabytes, and by 2025, it's projected to reach 163 zettabytes, up from 12 zettabytes in 2015. In addition, the cloud facilitates market adoption by integrating data science platforms, with key companies investing heavily in developing a cloud integration platform. With cloud computing, you can access an infinite pool of computer resources. Servers from cloud providers like Amazon Web Services can have up to 96 virtual CPU cores and about 768 GB of RAM. More than a hundred servers can be started and halted instantly in the autoscaling group. Cloud providers now provide more than just processing power; they also provide robust environments for data analytics. Additionally, increased investments in R&D have resulted in rapid technological growth. Since there are now more enterprises than ever before, there is a greater need for tools that boost production and efficiency. Data science platforms are in high demand because they simplify ML model training, development, scaling, and deployment, making them essential to the growth of any modern organization. Market expansion may be attributed to the proliferation of cutting-edge technologies like artificial intelligence (AI), edge computing, the Internet of Things (IoT), machine learning (ML), and streaming analytics.
Data Science Platform Industry Segmentation
Component
• Platform
• Services
o Professional
o Managed
o Support & Maintenance
o Deployment & Integration
Deployment
• On-Premise
• Cloud
• Hybrid
Enterprise Size
• SMEs
• Large
End User
• IT & Telecommunication
• Healthcare
• BSFI
• Manufacturing
• Retail
• Others
Application
• Marketing & Sales
• Customer Support
• Financing & Accounting
• Others
Data Science Platform Market Regional Segmentation
North America
o U.S.
o Canada
o Mexico
Europe
o Germany
o U.K.
o France
o Spain
o Italy
o Rest of Europe (RoE)
Asia Pacific (APAC)
o Japan
o China
o India
o South Korea
o Rest of APAC
Latin America
o Argentina
o Brazil
o Rest of Latin America
Middle East & Africa
o South Africa
o UAE
o Saudi Arabia
o Rest of MEA
Component Insights
Platform to Validate Their Presence at the Most Due to Overall Trend of Repeated Service
Based on components, the market can be broken down into platforms and services.
In terms of percentage of total revenue, platforms dominated in 2022. This is because of the general trend toward using data technologies in corporate settings. Businesses are investing in products that will help them achieve consistency and repeatability. Data science platforms can help get you there.
Growth in the services industry is forecasted for the foreseeable future. Training, consultation, deployment, integration, maintenance, and support are just some of the services offered by market leaders. More and more businesses are looking for methods to incorporate data science platforms into their working environment to reap the platform's productivity and efficiency benefits since this platform offers huge growth prospects. As a result, many people are turning to these services to help them successfully incorporate new technologies into their everyday lives.
Deployment Insights
Cloud Deployment to Gather Largest Revenue Share Owing to Faster & Reliable Service
The market can be split into on-premise, cloud, and hybrid based on deployment.
The cloud-based deployment category currently accounts for the largest share of the data science platform market and is predicted to increase at the highest CAGR during the forecast period. This is because real-time data transmission enabled by cloud-based deployment helps improve services and company operations. Companies are using cloud-based solutions that increase consumer engagement and retention. Demand for cloud-based systems will likely increase due to their speed and convenience.
Despite the proliferation of cloud solutions and expanded features, on-premises deployment continues to see strong demand. However, the primary reason businesses continue to invest in on-premises solutions is to ensure the security of their data.
Regional Insights
North America to Dominate Global Utilization Owing to the Presence of Major Players
Based on location, the global market can be split across North America, Europe, Asia Pacific, Latin America, the Middle East and Africa.
Over the projection period, North America is anticipated to have the largest revenue share. The presence of major players from various sectors is anticipated to propel market expansion. Increased spending on cutting-edge technologies also contributes to a rise in demand. The presence of major companies in the market contributes to the region's increased revenue share. Canada and the United States invest heavily in cutting-edge technology that can leverage data to aid commercial decision-making. The abundance of capital-intensive enterprises in the area also helps the data science platform develop. As more businesses in the region become familiar with these platforms and their advantages, more are using them as part of their standard operating procedure.
The European market was the second largest after the Americas. More and more local firms are using data-driven digital transformation tools to help them expand. The European market is also predicted to be dominated by Germany and the United Kingdom. It is anticipated that rapid digital transformation, the use of cutting-edge technologies, the rollout of 5G infrastructure, and other factors will accelerate the uptake of data science platforms.
During the foreseen period, the Asia-Pacific area is anticipated to exhibit a high pace of expansion. Rapid expansion into new sectors is predicted for using Big Data analytics technologies. The governments of several countries, including China, South Korea, India, and others, are investing in data analytics technologies due to their widespread usefulness. Synaptic, a data analytics startup in India, secured USD 20 million in series B investment in May 2020. This has led to an increase in the number of data science and analytics firms in the area.
Data Science Platform Industry Analysis
There is an active startup ecosystem in the worldwide market. More than a hundred new businesses will likely be launched to provide cutting-edge answers for consumers. Strong competition in such a market would force established companies to release and distribute updated versions of their products regularly.
Market participants are coordinating their efforts to create cutting-edge technologies that satisfy customers' demands. For example, IBM Corporation, a technology firm, and Anaconda Inc., a Python data science platform supplier, formed a partnership in June 2020. Open-source, AI-powered solutions are made more accessible through a collaborative effort.
Data Science Platform Market Recent Developments
• In October 2022, with the release of the Diamondback tape library, IBM has introduced an LTO-formatted product that can store up to 27 PB in a single server rack.
• In June 2022, the acquisition of Kamakura Corporation by SAS Institute enables the company to provide expert integrated risk solutions, particularly in Asset Liability Management (ALM), to industries including banking and finance.
• In June 202, Databricks improved the data-sharing process by introducing novel features and capabilities, such as an analytic marketplace, encrypted data cooperation, and intelligent cost reduction. Significant enhancements to data warehousing, governance, and mining are also introduced.
Global Data Science Platform Market Prominent Players
• SAS Institute Inc. (U.S.)
• The Mathworks Inc. (U.S.)
• Dataiku (U.S.)
• IBM Corporation (U.S.)
• Alteryx Inc. (U.S.)
• Oracle Corporation (U.S.)
• DataRobot Inc. (U.S.)
• Databricks (U.S.)
• TIBCO Software Inc. (U.S.)
• Google Inc. (U.S.)
• Microsoft Corporation (U.S.)
• Datarobot Inc (U.S.)
Frequently Asked Questions (FAQs)
At what rate will the Data Science Platform Market Expand?
According to Objective Market Research, throughout the projection period, the market for data science platforms is expected to grow at a CAGR of 29.5%.
What are the factors driving the global Data Science Platform Market?
The global data science platform market will grow during the forecast period owing to the development of big data technologies and the significance of gathering and utilizing data for decision-making during the forecast period.
Which segment accounted for the largest Data Science Platform Market share by End User?
Throughout the projection horizon, the IT and telecommunications industries will experience the highest increase in market share. This domain will likely grow in prominence as the emphasis on customer service increases.
What region holds the major share in the global market scape?
North America is expected to have the greatest revenue share during the forecast period. It is anticipated that the presence of significant actors from various industries will stimulate market expansion. Increasing expenditures on innovative technologies also contribute to demand growth.
Which are the dominating players in the market during the forecast period?
Some market leaders in the global data science platform market are SAS Institute Inc. (U.S.), The Mathworks Inc. (U.S.), Dataiku (U.S.), IBM Corporation (U.S.), Alteryx Inc. (U.S.), and Oracle Corporation (U.S.), among others.
*Our reports are available on a region/wise and chapter/wise basis as well. For any additional personalization contact our sales representative directly at sales@objectivemarketresearch.com
Table of Content
1. Introduction
1.1 Market Definition
1.2 Objective of the Study
1.3 Market Scope
1.4 Years Considered in the Study
1.4.1 Historic Year: 2019-2021
1.4.2 Base Year: 2022
1.4.3 Forecast Period: 2023-2030
1.5 Currency Used in the Study
1.6 Boundaries for the Study
1.7 Collaborators/Stakeholders/Benefactors
2. Research Methodology
2.1 Research Outline
2.2 Data Collection Methods
2.3 Data Sources
2.3.1 Secondary Sources
2.3.1.1 Paid Sources
2.3.1.2 Unpaid Sources
2.3.2 Primary Sources
2.4 Market Estimation Methodology
2.4.1 Top-Down Approach
2.4.2 Bottom-Up Approach
2.5 Data Triangulation
2.6 Assumptions of the Study
2.7 Limitations of the Study
3. Executive Summary
3.1 Market Outlook
3.2 Analysts Perspective
4. Market Overview
4.1 Market Dynamics
4.1.1 Drivers
4.1.1.1. Increasing Flow of Data
4.1.1.2. Rising Demand for Big Data Integration
4.1.2. Restrain
4.1.2.1. Low Number of Professionals
4.1.3. Opportunities
4.1.3.1. Advanced Solutions within the Healthcare Sector
4.1.4. Impact of Market Dynamics
4.2. Impact of COVID-19 pandemic
4.3. Value Chain Analysis
4.4. Porter’s Five Forces Analysis
4.4.1. Bargaining Power of Buyers
4.4.2. Bargaining Power of Suppliers
4.4.3. Threat of Substitution
4.4.4. Threat of New Entrants
4.4.5. Competitive Rivalry
5. Global Data Science Platform Market Analysis & Forecast, by Component from 2019-2030 (in USD million)
5.1. Platform
5.2. Services
5.2.1. Professional
5.2.2. Managed
5.2.3. Support & Maintenance
5.2.4. Deployment & Integration
6. Global Data Science Platform Market Analysis & Forecast, by Deployment from 2019-2030 (in USD million)
6.1. On-Premise
6.2. Cloud
6.3. Hybrid
7. Global Data Science Platform Market Analysis & Forecast, by Enterprise Size from 2019-2030 (in USD million)
7.1. SMEs
7.2. Large
8. Global Data Science Platform Market Analysis & Forecast, by End User from 2019-2030 (in USD million)
8.1. IT & Telecommunication
8.2. Healthcare
8.3. BSFI
8.4. Manufacturing
8.5. Retail
8.6. Others
9. Global Data Science Platform Market Analysis & Forecast, by Application from 2019-2030 (in USD million)
9.1. Marketing & Sales
9.2. Customer Support
9.3. Financing & Accounting
9.4. Others
10. Global Data Science Platform Market Analysis & Forecast, by Region from 2019-2030 (in USD million)
10.1. North America
10.1.1. North America Data Science Platform Market Analysis & Forecast, By Country
10.1.1.1. U.S.
10.1.1.2. Canada
10.1.1.3. Mexico
10.1.2. North America Data Science Platform Market Analysis & Forecast, By Component
10.1.3. North America Data Science Platform Market Analysis & Forecast, By Deployment
10.1.4. North America Data Science Platform Market Analysis & Forecast, By Enterprise Size
10.1.5. North America Data Science Platform Market Analysis & Forecast, By End User
10.1.6. North America Data Science Platform Market Analysis & Forecast, By Application
10.2. Europe
10.2.1. Europe Data Science Platform Market Analysis & Forecast, By Country
10.2.1.1. Germany
10.2.1.2. UK
10.2.1.3. France
10.2.1.4. Spain
10.2.1.5. Italy
10.2.1.6. Rest of Europe (RoE)
10.2.2. Europe Data Science Platform Market Analysis & Forecast, By Component
10.2.3. Europe Data Science Platform Market Analysis & Forecast, By Deployment
10.2.4. Europe Data Science Platform Market Analysis & Forecast, By Enterprise Size
10.2.5. Europe Data Science Platform Market Analysis & Forecast, By End User
10.2.6. Europe Data Science Platform Market Analysis & Forecast, By Application
10.3. Asia-Pacific (APAC)
10.3.1. Asia-Pacific Data Science Platform Market Analysis & Forecast, By Country
10.3.1.1. Japan
10.3.1.2. China
10.3.1.3. India
10.3.1.4. South Korea
10.3.1.5. Rest of the APAC
10.3.2. Asia-Pacific Data Science Platform Market Analysis & Forecast, By Component
10.3.3. Asia-Pacific Data Science Platform Market Analysis & Forecast, By Deployment
10.3.4. Asia-Pacific Data Science Platform Market Analysis & Forecast, By Enterprise Size
10.3.5. Asia-Pacific Data Science Platform Market Analysis & Forecast, By End User
10.3.6. Asia-Pacific Data Science Platform Market Analysis & Forecast, By Application
10.4. Latin America
10.4.1. Latin America Data Science Platform Market Analysis & Forecast, By Country/Region
10.4.1.1. Argentina
10.4.1.2. Brazil
10.4.1.3. Rest of Latin America
10.4.2. Latin America Data Science Platform Market Analysis & Forecast, By Component
10.4.3. Latin America Data Science Platform Market Analysis & Forecast, By Deployment
10.4.4. Latin America Data Science Platform Market Analysis & Forecast, By Enterprise Size
10.4.5. Latin America Data Science Platform Market Analysis & Forecast, By End User
10.4.6. Latin America Data Science Platform Market Analysis & Forecast, By Application
10.5. Middle East & Africa
10.5.1. Middle East & Africa Data Science Platform Market Analysis & Forecast, By Country/Region
10.5.1.1. South Africa
10.5.1.2. UAE
10.5.1.3. Saudi Arabia
10.5.1.4. Rest of Middle East & Africa
10.5.2. Middle East & Africa Data Science Platform Market Analysis & Forecast, By Component
10.5.3. Middle East & Africa Data Science Platform Market Analysis & Forecast, By Deployment
10.5.4. Middle East & Africa Data Science Platform Market Analysis & Forecast, By Enterprise Size
10.5.5. Middle East & Africa Data Science Platform Market Analysis & Forecast, By End User
10.5.6. Middle East & Africa Data Science Platform Market Analysis & Forecast, By Application
11. Competitive Landscape
11.1. Market Share Analysis (2022)
11.2. Market Positioning of Top Players (2022)
11.3. Key Developments & Growth Strategies (2020-2022)
11.3.1. Product Launches
11.3.2. Merges, Collaborations & Agreements
11.3.3. Expansion
11.4. SWOT Analysis
12. Company Profiles (Business Overview, Products Offered, Financial Details*, Recent Developments)
12.1. SAS Institute Inc. (U.S.)
12.1.1. Company Snapshot
12.1.2. Business Overview
12.1.3. Financial Data
12.1.4. Key Products Offered
12.1.5. Recent Developments
12.2. The Mathworks Inc. (U.S.)
12.3. Dataiku (U.S.)
12.4. IBM Corporation (U.S.)
12.5. Alteryx Inc. (U.S.)
12.6. Oracle Corporation (U.S.)
12.7. DataRobot Inc. (U.S.)
12.8. Databricks (U.S.)
12.9. TIBCO Software Inc. (U.S.)
12.10. Google Inc. (U.S.)
12.11. Microsoft Corporation (U.S.)
12.12. Datarobot Inc (U.S.)
12.13. Others
13. Appendix
13.1. Currency Exchange Rate to USD
13.2. Abbreviations
* Financial details captured might be subjected to information available and not be given for privately-held companies or for companies that do not report it in the public domain