Data Science Platform Market

Global Data Science Platform Market Size (2023 - 2028)

The Global Data Science Platform Market was worth US$ 24.8 billion in 2022, and it is estimated to reach a valuation of US$ 136.3 billion by the end of 2028, expanding at an annual growth rate of 32.8% between 2023 and 2028.

A Data Science Platform is software that includes different type of technologies for machine learning and other advanced analytics uses. It is an environment for conducted data science work, which basically includes coding and the deployment of the code models as well as aggregation and use of data from various resources. Data Science provides a structure in which the entire lifecycle of the data science projects takes place. This platform consists of the tool and resources which is required to complete each phase of the data science project lifecycle. It brings together people, tools, resources and other necessary products that used cross the data science lifecycle from development to deployment. Data Science allows all the resources in one centralized place that allow data scientist and teams to speed up the model deployment process. Data Science platform helps organization to find when and where their products sell bests. Also can help in deliver right product at right time and also helps company to develop new product in order to meet customer’s demand. Owing to the various features and benefits to the business, the demand of the data science platform is going to increase which will further boost the growth of data science platform market.

Market Drivers:

The driving force of the Data Science Platform Market is the various tools and resources offered by data science platform for business growth.

The telecom companies majorly function with broad communication networks and infrastructure thus operates full data flow. Therefore, the need of the data science is increasing in this sector in order to analyze and process large volume of data effectively and efficiently. Further, the cloud is catering to market adoption with data science platform integration, where major players are significantly developing the cloud integration platform. For example, Google Cloud offers a platform which is called “BigQuery”. BigQuery is a server less and scalable data warehouse that offers Data Scientist the ability to store and analyze petabytes of the data in a single platform.

The rising awareness of benefits of data science in the business is driving the demand of the data science platform in developed as well as developing nations around the world.

Furthermore, during the pandemic, cloud computing has emerged as an efficient model that helps in facilitating             some of the most crucial transformation businesses are undergoing. According to the cloud surveys conducted by Flexera, globally around 50% of organization that includes both SMBs or enterprises plan to increase their cloud usage  in the light of the coronavirus crisis, thereby the demand of the data science platform will increasing in the near future.

Market Restraints:

Data scientist is one who is skilled enough to better utilize all the tools and resources of data science platform in order to get best results and organization growth. The lack of such desired skilled scientist is hampering the growth of the data science platform market.

GLOBAL DATA SCIENCE PLATFORM MARKET REPORT COVERAGE:

Market Segmentation:

Global Data Science Platform Market - By Services:

• Managed Services
• Professional Services

Based on Services, the Data Science Platform Market is segmented into Managed Services and Professional Services. Professional Service segment is expected to dominate the market due to growing complexity of operations and the increasing deployment of Business Intelligence platform.

Global Data Science Platform Market - By Business Function:

• Marketing

• Sales
• Logistics
• Customer Support

Based on Business Function, the Marketing as well as Sales segment holds the largest market share because by using data science in marketing and sales department can get more insights to the buyer’s mind and spend marketing budget accordingly, thereby generating more Return on Investment (ROI). In addition to it, the other factors such as reduced financial risks due to precise spending calculation, more predictable revenue generation, and enhanced customer experience is contribution to the adoption of Data Science in this segment which will boost the Data Science Platform during the forecast period.

Global Data Science Platform Market - By Mode of Deployment:

• Cloud
• On-Premises

Based on mode of deployment, the Data Science Platform Market is segmented into Cloud and On-Premises. Cloud segment is expected to dominate the market during the forecast period due to deploying cloud based data science platform helping businesses more efficiently process and report data findings, it enhance collaborations and provide decision makers faster access to business intelligence. Owing to these benefits the cloud segment drives the growth of data science platform market in coming years.

Global Data Science Platform Market - By Industry:

• Banking, Financial Services & Insurance (BFSI)
• Telecom and IT
• Retail and e-commerce
• Healthcare and Life sciences
• Manufacturing
• Energy and Utilities
• Media and Entertainment
• Transportation and Logistics
• Government
• Others (travel and hospitality, education, and research)

Based on Industry, the Data Science Platform Market is segmented into Banking, Financial Services & Insurance (BFSI), Telecom and IT, Retail and e-commerce, Healthcare and Life sciences, Manufacturing, Energy and Utilities, Media and Entertainment, Transportation and Logistics, Government and Others. Among these sectors, healthcare segment is expected to dominate the market in the upcoming years. Data science platform provides various medical research communities that can generally share, integrate and analyze historical, patient-level data from academic and industry phase III clinical trials. Owing to such a rich data set as a part of data science that undoubtedly will help pharmaceutical research and development segment.

Regional Analysis:

The Global Data Science Platform Market has been categorized in four regions: North America, Europe, Asia-Pacific, and RoW (Rest of the World). 

North America accounted for the largest market share and will continue to dominate the market during the forecast period due to large enterprises, technical experts, and the increasing demand of the data platforms in this region. In United States large number of clinical documents in being produced annually, healthcare practitioners and doctors have significant data to base their research upon. Moreover, huge volume of health-related information are made accessible through large adoption of wearable technologies in this region, thus bringing new opportunities for the regions better and more informed healthcare system. Furthermore, the presence of capital-intensive industries across this region proves to be beneficial for the growth of the data science platform. Additionally, the presence of some of the established players such as Google Inc, IBM corporation, Microsoft, Cloudera etc are leveraging powerful machine learning and data science technologies that can turn data into actionable insights further drives the growth of the data science platform market during the forecast period.

After North America, Europe holds the largest share of the Data Science Platform Market due to rising data-driven digital transformation and the presence large number of industries that are adopting these technologies to their systems is driving the growth of the market.

Asia-Pacific is expected to become the fastest growing market due to increasing demand of data processing is boosting the demand of the data science platform in this region. Moreover, the investments by the major companies are driving the growth of the data science market in this region. Also the increasing awareness of the benefits of these platforms, enterprises has started integrating data science platforms into their existing operation system in order to gain competitive advantage in the regions market place which further drives the demand of the data science platforms in this region. In this region, China is actively investing in the data science sector while implementing the technologies.

Leading Company:

IBM had the largest share of the world’s data science platform market in terms of sales revenue in 2020.

Covid-19 Impact on Global Data Science Platform Market: 

The Global Data Science Platform Market has been significantly impacted by the COVID-19 outbreak. The pandemic has adversely affected several businesses and the supply chains which results to economic loss. The implementation of new projects has delayed throughout the world, which, in turn led to decline the demand of the data science platform. Also due to economic loss, industrialist has either cancelled or postponed their plan of data science platform integration which has affected the data science market negatively. Due to unpredictable behavior of the COVD-19 and its impact on the business operations is fueling the demand of the data science platform which further boosts the growth of the market in the projected period in order to predict upcoming business challenges.

Key Players:

Some of the leading companies operating in the Global Data Science Platform Market are 

1. IBM Corporation (US)
2. Microsoft Corporation (US)
3. Alphabet Inc. (Google) (US)
4. Altair Engineering, Inc. (US)
5. Alteryx, Inc. (US)
6. MathWorks  (Australia)
7. SAS Institute Inc. (US)
8. RapidMiner, Inc. (US)
9. Cloudera, Inc. (US)
10. Anaconda, Inc. (US)

Recent Developments:

In May 2021, Google Cloud has announced the general availability of Vertex AI, which is a managed machine learning platform that allows companies to accelerate the deployment and maintenance of artificial intelligence models.

In April 2021, Cloudera (the enterprise data cloud company) has announced its collaboration with NVIDIA. This collaboration allowed Cloudera Data Platform to integrate the “RAPIDS Accelerate for Apache Spark 3.0” in order to Accelerate Data analytics and AI in the cloud.