Data Science Platform Market Share Analysis by Component (Platform, Services), Deployment Mode (Cloud, On-Premises), Organization Size (SMEs, Large Enterprises), Business Function (Marketing, Sales, Logistics, Finance & Accounting, Customer Support, Business Operations), Industry Vertical (IT & Telecommunication, Healthcare, BFSI, Manufacturing, Retail & E-commerce, Energy and Utilities, Government) - Global Industry Trends and Growth Forecast to 2030

Market Overview

The global data science platform market was valued at $92.4 billion in 2021, and it is projected to reach $708.8 billion by 2030, growing at a significant CAGR of 25.4% between 2021 and 2030. This is primarily attributed to the rapid growth in demand for big data technologies along with the increasing penetration of data analytic platforms in various industries. Moreover, the rising volume of data and obtaining access to organizational data from many departments throughout a business is projected to drive the market.

Data science platforms are becoming increasingly popular across the world. The program provides open-source tools with considerable flexibility and scalability of computing resources. It is also simple to align with diverse data architectures. Aside from that, the platform supports version control, allowing the data science team to collaborate on projects without losing previously completed work. Such advantages contribute significantly to the market growth in the coming years.

The surging volume of organization data, fast technical advances, and falling average selling costs of smart devices all contribute to the production of vast amounts of unorganized and unstructured data. Over 80% of the data collected by an organization is not stored in a traditional relational database. It is instead hidden in unstructured papers, social media posts, machine logs, photographs, and other sources. The tremendous expansion of data gives chances for companies to obtain new insights, which has boosted the demand for innovative tactics and processes. This, in turn, helps fuel the industry growth over the forecast period.

Data Science Platforms Hold Majority of Revenue Share

The market is divided into platforms and services based on the component segment. The platforms category accounted for a larger revenue share, of more than 80% in 2021. This is because large and medium-sized organizations are increasingly utilizing data technologies, and they are focusing on developing products that deliver consistency and efficiency, as a result of implementing data science platforms.

Whereas, the services category is expected to grow at a significant CAGR over the next few years. Some of the key services offered by well-known companies in this field include training, deployment, consulting, integration, maintenance, and support. Since data science platforms provide tremendous development opportunities, hence more businesses are looking for ways to include them in their working environments in order to enhance efficiency and productivity. As a result, these services are widely employed by firms to effectively integrate the platform into their prevailing environment successfully.

On-Premises Deployment Is Gaining Popularity Among Organizations

The on-premises category accounted for the largest revenue share in 2021, in the data science platform market, owing to the surging deployment of data science solutions on-premises. The on-premises deployment approach is used by enterprises in highly regulated verticals such as BFSI, healthcare and life sciences, and manufacturing. Furthermore, major organizations with adequate IT resources are likely to choose the on-premises deployment strategy, as it is the most dependable deployment strategy, allowing them to maintain a high level of control and security.

Large enterprises held the largest market share in 2021, and this trend is expected to continue during the forecast period, due to the increasing popularity of cloud technologies among these enterprises. Large organizations collect massive volumes of data from their diversified consumer base. In large enterprises, data is critical for measuring their overall performance. These corporations utilize data science platforms to evaluate data from a range of sources, including social media feeds, sensors, and webcams. Each record must be handled while keeping its link to other data and its chronological sequence in mind.

Surging Volumes of Data

With the increased use of social media, multimedia, and IoT, which have resulted in an overwhelming flow of data in either structured or unstructured format, the volume of data gathered by enterprises is constantly expanding. For example, about 90% of the world's data has been produced in the last two years. Moreover, machine-generated and human-based data are growing at a rate that is around 10 times faster than traditional commercial data.

For instance, the growth rate of the adoption of machine data is exponential and 50 times higher. Consumer-driven and -oriented data predominates. Consumers who are "always-on," generate most of the data around the globe. Nowadays, the majority of individuals spend 4–6 hours each day generating and consuming data via a range of gadgets and (social) applications. Every time people swipe, click, or send a message, fresh information is added to a database somewhere in the world. Because everyone now has a smartphone, enormous volumes of data are being created.

Growing Adoption of Data Science in the BFSI Industry

The BFSI sector held the largest revenue share, of around 19.2%, in 2021, and it is expected to grow at a significant growth rate in the next few years in the data science platform market. The implementation of data science in banking and financial companies has become more than necessary. Data science technology has become a trend in every industry because of how well it works and how readily it simplifies tasks. Moreover, banks will be able to focus their resources more efficiently, make better judgments, and enhance their performance in accordance with their standard objectives with the aid of data science.

Banks have a lot of data from their customers and clients, which is becoming tough to manage. Banks save even little information about their consumers, which must be kept safe. As a result, banks are obligated to gather, analyze, and retain huge volumes of data. Digital banking has grown in popularity and is now commonly utilized. Banks can readily obtain information about customer interactions and preferences through online transactions, and data science may use this data to enhance decision-making processes and create new revenue-generating options for the industry.

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Technological Advancements in Technologies

Rapid technological improvements are taking place as a result of increasing research and development spending. As organizations grow, there is a greater demand for technologies that can increase productivity and efficiency. Also, the use of platforms and software is rising due to the prevalence of technologies like artificial intelligence (AI), machine learning (ML), and the internet of things (IoT). As data quantities rise every day, modern data handling systems and solutions are crucial for the growth of enterprises, which would drive product demand in the market throughout the projected period.

North America Is Principal Revenue Contributor

North America is the leader in the market for data science platforms because of its existing infrastructure, a large number of R&D activities, and the presence of key industry players across the region. Additionally, it is predicted that efficient aftersales services are available and the existence of numerous capital-intensive enterprises in North America boost the demand for data science platforms. As organizations become more aware of the benefits of these platforms, they continue to incorporate them into their existing operating systems in order to obtain a competitive advantage in the regional market.

Top Players in the Data Science Platform Market Are:

• IBM
• Google
• Microsoft
• SAS
• Amazon Web Services Inc.
• The MathWorks, Inc.
• Cloudera Inc.
• TIBCO Software Inc.
• Teradata
• Alteryx Inc.

Global Data Science Platform Market Size Breakdown by Segment

The study offers a comprehensive market segmentation analysis along with market estimation for the period 2017-2030.

Based on Component

•   Platform
• Services
  • Professional Services
  • Support & Maintenance
  • Consulting
  • Deployment & Integration

Based on Deployment Mode

• Cloud
• On-Premises

Based on Organization Size

• Small & Medium Sized Enterprises (SMEs)
• Large Enterprises

Based on Business Function

• Marketing
• Sales
• Logistics
• Finance & Accounting
• Customer Support
• Business Operations

Based on Industry Vertical

• IT & Telecommunication
• Healthcare
• BFSI
• Manufacturing
• Retail & E-commerce
• Energy and Utilities
• Government

Geographical Analysis

• North America
  • U.S.
  • Canada
• Europe
  • U.K.
  • Germany
  • France
  • Spain
  • Italy
• Asia-Pacific
  • China
  • India
  • Japan
  • South Korea
  • Australia
• Latin America
  • Brazil
  • Mexico
• Middle East and Africa
  • Saudi Arabia
  • South Africa