Data science platforms are reliable solutions for the analysis & processing of large data volumes. These platforms allow data scientists to collaborate & work within the same digital environment and convert data into valuable insights.
Over the years, the utilization of data science platforms has surged significantly. Companies are increasingly deploying state-of-the-art technologies like automation & digitalization, i.e., generating massive amounts of data while making business operations complex. As a result, the need for more effective data science platforms is rapidly growing worldwide.
The Global Data Science Platform Market is projected to grow at a CAGR of around 27% during the forecast period, i.e., 2022-27. The growth of the market would be propelled mainly by the mounting focus of enterprises on becoming more competitive in the rapidly changing industry dynamics, i.e., leading to the growing adoption of cutting-edge technologies, including data science platforms, across different businesses.
Moreover, the mounting awareness among businesses of various benefits of these platforms, viz. the flexibility & scalability of computing resources, compatibility with different types of data architecture, support for version control to allow for project collaborations without any loss of work, etc., is also contributing to the expansion of the data science platform industry.
|Study Period||Historical Data: 2017-20|
|Base Year: 2021|
|Forecast Period: 2022-2027|
|Regions Covered||North America: The US, Canada, Mexico|
|Europe: Germany, The UK, France, Russia, Rest of Europe|
|Asia-Pacific: China, Japan, India, Singapore, South Korea, Rest of Asia Pacific|
|South America: Brazil, Rest of South America|
|Middle East & Africa: UAE, Saudi Arabia, South Africa, Rest of The Middle East & Africa|
|Key Companies Profiled||
ActionIQ, Alphabet Inc. (Google), Alteryx Inc., Amazon Web Services, Inc., Anaconda, Inc., Cloudera, Inc., Domino Data Lab, Inc., IBM Corporation, H2O.ai, MathWorks, Microsoft Corporation, SAP SE, SAS Institute, Inc., Snowflake Inc., Teradata Corporation, Others
|Unit Denominations||USD Million/Billion|
Furthermore, the increasing dependence of companies on ML (Machine Learning), data-intensive business strategies, and cloud-based analytical solutions is also projected to positively impact the dynamics of the data science platform market in the coming years.
With growing data volumes in the healthcare sector due to clinical databases, rising use of wearables, and EMRs (Electronic Medical Records), healthcare professionals are increasingly using data science platforms in order to achieve faster disease diagnosis, practice preventive medicine, & identify new therapeutics, which, in turn, is fueling the overall growth of the industry.
Additionally, the surging prevalence of autonomous vehicles, growing requirements for enhancing logistics efficiency, and the rapidly booming entertainment sector are further creating new directions for data science platform developers to witness lucrative prospects in the future.
Nevertheless, the growing instances of cyberattacks due to a rapid rise in online transactions are escalating the use of data science platforms in the BFSI (Banking, Financial Services, & Insurance) sector in order to detect fraudulent acts and prevent cybercrimes, thereby driving the Global Data Science Platform Market.
Based on Deployment:
Of both deployment methods, Cloud-based analytics is gaining traction and contributing significantly to the growth of the Global Data Science Platform Market. Technologies like AI (Artificial Intelligence), NLP (Natural Language Processing), & Cloud computing are transforming how companies interact with analytics platforms. Cloud-based platforms help companies eliminate the need for substantial investments in establishing physical infrastructure & gathering human expertise required for on-premise analytics solutions. In addition, IT maintenance costs for implementing cloud-based tools or applications are relatively less than on-premise platforms.
Moreover, there's no limitation of local networks with cloud analytics, which allows for better data accessibility, as employees can remotely access company information. Furthermore, cloud-based data platforms also provide scalable resources through numerous subscription models, offer unlimited storage as per business requirements, can arrange & deploy multiple virtual servers, and help manage demand surges without the need for investments in hardware. Hence, using cloud platforms, more and more organizations are opting for cloud-based analytics, which also helps them save their time & money on upgradation, and, consequently, driving the Global Data Science Platform Market.
Based on End-Users:
Here, the healthcare sector is emerging as a prominent end-user of the Global Data Science Platform Market. Challenges like lack of better patient care, increasing treatment costs, and less patient retention & engagement are driving the implementation of data science platforms across the healthcare industry in order to enable medical practitioners extensively analyze, process, integrate, and share patient data and, in turn, provide better care & treatment to them.
More and more healthcare establishments are deploying data science platforms to enhance the accuracy & efficiency of diagnostics through powerful machine learning algorithms, thereby reducing diagnostic failure rates.
Moreover, several government initiatives & substantial investments in the healthcare sector are further bringing innovations and promulgating the adoption of data analytics platforms across healthcare facilities, i.e., enabling medical professionals to manage & interpret critical insights generated from various clinical studies while efficiently studying historical patient data to devise appropriate methods, tools, & technologies in order to achieve positive outcomes. Hence, these aspects are creating new avenues for the Global Data Science Platform Market to witness significant expansion across the healthcare sector in the years to come.