Global Data Science Platform Market By Component (Platform (Without Services) and Services), By Deployment Type (On-premises and Cloud), By Enterprise Size (Large Enterprise and Small & Medium Enterprise), By Application (Marketing & Sales, Logistics, Customer Support, Finance & Accounting and Others), By End User (BFSI, Energy & Utilities, Healthcare, Retail & eCommerce, Government & Defense, IT & Telecommunication, Manufacturing and Others), By Region, Industry Analysis and Forecast, 2020 - 2026
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Get in-depth analysis of the COVID-19 impact on the Data Science Platform Market
Market Report Description
The Global Data Science Platform Market size is expected to reach $165.5 billion by 2026, rising at a market growth of 27% CAGR during the forecast period. The data science platform can be considered as a technology of software that is being extensively utilized by industries today. This software includes several innovations for numerous advanced analytics and machine learning. It enables data scientists to design strategies, uncover insights from data, and impart those experiences all through a venture inside a single situation. The projects performed in data science include numerous instruments designed at each step of the data modeling process.
Data Science Platform Market Size, By Deployment Type, 2020-2026
The adoption of data science platforms is expanding quickly today. The software gives high adaptability to open source instruments and scalability of computer resources. It can also be handily aligned with different data architecture. Besides, the platforms empower version control, which empowers the data science team to collaborate on ventures without losing the work that has recently been done. Such advantages are significantly adding to the development of the market.
Data Science Platform Market Share, By Industry Vertical, 2019
The COVID-19 (Coronavirus Disease) pandemic has affected each industry. The pandemic has also influenced the data science industry. The models prior utilized for estimating or segmentation is failing because of rapid changes in online traffic or shopping trends. The borders have been locked down, and the supply chain has been disrupted. Hence, organizations are presently focusing on laying short, medium, and long-term data-driven plans to make educated choices.
The organizations are amending the assumption made during data analysis. New cycles are being made. Data substitution, changes in traffic, focus on healthcare-related supply chains are some trends being seen in the market in the current situation. The most affected segment during the pandemic is healthcare. Experts in the healthcare sector are focusing on utilizing data from nations that were recently affected by the pandemic to make more exact choices.
|Market size value in 2019||USD 34.1 Billion|
|Market size forecast in 2026||USD 165.5 Billion|
|Historical Period||2016 to 2018|
|Forecast Period||2020 to 2026|
|Revenue Growth Rate||CAGR of 27% from 2020 to 2026|
|Number of Pages||343|
|Number of Tables||573|
|Report coverage||Market Trends, Revenue Estimation and Forecast, Segmentation Analysis, Regional and Country Breakdown, Competition Analysis, Companies Strategic Developments, Company Profiling|
|Segments covered||Component, Deployment Type, Enterprise Size, Application, End User, Region|
|Country scope||US, Canada, Mexico, Germany, UK, France, Russia, Spain, Italy, China, Japan, India, South Korea, Singapore, Malaysia, Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria|
Free Valuable Insights: Global Data Science Platform Market to reach a market size of $165.5 Billion by 2026
Based on Component, the market is segmented into Platform (Without Services) and Services. Based on Deployment Type, the market is segmented into On-premises and Cloud. Based on Enterprise Size, the market is segmented into Large Enterprise and Small & Medium Enterprise. Based on Application, the market is segmented into Marketing & Sales, Logistics, Customer Support, Finance & Accounting and Others. Based on End User, the market is segmented into BFSI, Energy & Utilities, Healthcare, Retail & eCommerce, Government & Defense, IT & Telecommunication, Manufacturing and Others. Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa.
KBV Cardinal Matrix - Data Science Platform Market Competition Analysis
The major strategies followed by the market participants are Partnerships and Acquisitions. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation and Google, Inc. are the forerunners in the Data Science Platform Market. Companies such as IBM Corporation, Alteryx, Inc., Cloudera, Inc., Altair Engineering, Inc., RapidMiner, Inc., SAS Institute, Inc., SAP SE, and The MathWorks, Inc. are some of the key innovators in the market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include IBM Corporation, Microsoft Corporation, Google, Inc., SAP SE, Altair Engineering, Inc., Alteryx, Inc., Cloudera, Inc., The MathWorks, Inc., SAS Institute, Inc., and RapidMiner, Inc.
Recent Strategies Deployed in Data Science Platform Market
» Partnerships, Collaborations, and Agreements:
- Oct-2020: Microsoft announced its collaboration with Udacity, for launching Machine Learning Engineer for Microsoft Azure Nanodegree Program. The launch was aimed to train learners in the careers of the future to stay relevant with the ever-evolving, tech-centric job market.
- Oct-2020: Microsoft came into collaboration with Novartis, a multinational pharmaceutical company. The collaboration was focused on using data & Artificial Intelligence (AI) for transforming the tradition that how medicines are discovered, developed, and commercialized and also establishing an AI Innovation Lab to empower associates to use AI across our business.
- Sep-2020: SAS signed a partnership agreement with RTI International, a non-profit organization. The partnership was aimed to tackle some of the world’s greatest challenges by bringing joint offerings to government agencies and other organizations. Following this partnership, the companies strengthened and improved services by integrating scientific rigor, subject matter expertise, advanced analytics, and technical and software products into comprehensive solutions.
- Aug-2020: Alteryx announced its partnership with UiPath, the leading enterprise Robotic Process Automation (RPA) software company. The partnership was aimed to speed up end-to-end automation across data-driven business processes. Together, the companies offer a solution that empowers business leaders, analysts, data scientists, and data engineers to increase operational efficiency and automate time-to-insights.
- Aug-2020: SAS India came into collaboration with Ganpat University (GUNI) for a two-year full-time Master of Business Administration (MBA) in Analytics. The objective of this program is to prepare future-ready managers who are well versed in Analytics and have experience in managing current tools and techniques in vogue. The program would impart skills in data integration, programming, visual business analytics, and machine learning, along with essential communication skills.
- Jun-2020: IBM Watson collaborated with Anaconda, Inc., a provider of the leading Python data science platform. The collaboration was focused on simplifying enterprise adoption of AI open-source technologies. The collaboration filled the AI and data science skills gap.
- Jun-2020: Microsoft collaborated with SAS, a developer of analytics software. The combination enabled customers to easily run their SAS workloads in the cloud, expanding business solutions. This partnership builds on SAS integrations across Microsoft cloud solutions for Azure, Dynamics 365, Microsoft 365, and Power Platform and supports the companies’ vision to further democratize AI and analytics.
- Mar-2020: SAS and Goa Institute of Management (GIM) hosted the First edition of Bitathon, a specially curated hackathon. This uses data analytics for forecasting Bollywood blockbusters. The hackathon’s key objective was to create managers who understand the complex business ecosystem and can work with the new norm of data-driven decision making.
- Mar-2020: SAS India announced its association with the Dhirubhai Ambani Institute of Information and Communication Technology (DA-IICT) for a two-year full-time Master of Science in Data Science (M.Sc. Data Science). The program was designed for addressing the new paradigm of fact-based decision making associated with the advent of Big Data.
- Feb-2020: Alteryx announced its collaboration with PwC U.S., a global network of firms delivering world-class assurance, tax, and consulting services. Following the collaboration, the Alteryx data science, analytics, and process automation platform was integrated with PwC's consulting for accelerating digital transformation for major organizations.
- Jan-2020: Google Cloud teamed up with Catalytic Data Science, a leading provider of life sciences R&D workflow solutions as a technology. The integration resulted in filling a long-standing gap within the life sciences R&D IT marketplace.
- Oct-2019: MathWorks in collaboration with Coursera, the world’s leading online learning platform, announced a joint effort for addressing the data science skills gap. MathWorks developed a series of courses named “Practical Data Science with MATLAB,” with the first course, “Exploratory Data Analysis with MATLAB”.
- Apr-2019: Google Cloud partnered with Qubole, data activation, and processing firm. The partnership enhanced user experience in the field of data science and engineering. Also, the companies got the option to deploy a new enterprise analytics service with a better user experience.
- Mar-2019: Alteryx and Thomson Reuters announced a partnership with ONESOURCE Tax Automation Suite. The partnership was focused on streamlining the data Analysis for Tax Professionals.
- Feb-2019: RapidMiner came into partnership with Talend, a company that offers a single suite of cloud apps for data integration and data integrity. The partnership aimed to help data science-focused organizations to operationalize predictive models in large-scale enterprises such as real-time customer experience, predictive maintenance, and fraud detection.
» Acquisition and Mergers:
- Oct-2020: SAP took over Emarsys, an omnichannel customer engagement platform provider. The acquisition boosted SAP's commerce offering and helped customers in delivering omnichannel engagements in real-time.
- Sep-2020: Altair acquired Ellexus, an input/output (I/O) profiling company. The acquisition integrated Ellexus' tools into the storage-aware scheduling functionality of Altair PBS Works. Ellexus also complemented Altair by providing per-job storage agnostic file and network I/O real-time monitoring to identify I/O latencies and bottlenecks to Altair’s scheduling technology.
- Fb-2020: Google Cloud announced the acquisition of Looker, a company that markets a data exploration and discovery business intelligence platform. The acquisition strengthened Google Cloud's analytics and data warehouse capabilities, including BigQuery, enabling its customers to address some of their toughest business challenges, faster all while maintaining complete control of their data.
- Oct-2019: Alteryx, Inc. acquired Feature Labs, a data science software company that automates feature engineering for machine learning and artificial intelligence (AI) applications. The acquisition empowered every data worker to fill the data science and machine learning talent gap.
- Sep-2019: Cloudera acquired Arcadia Data, Inc., a company that provides an advanced data analytics platform. The acquisition provides time-to-insight for Cloudera customers and drives the future of the enterprise data cloud for businesses that need to solve complex data management and analytic use cases.
- Jul-2019: IBM completed the acquisition of Red Hat, a software company that provides open-source software products to enterprises. The combination of the two companies bolstered innovation by offering a next-generation hybrid multi-cloud platform.
- Apr-2019: Alteryx took over ClearStory Data, a company that provides solutions for enabling business users to discover, analyze, and consume data at scale from different data sources. The acquisition enabled Alteryx in becoming a leading innovator of a code-free platform for citizen data scientists and the analytics market.
- Feb-2019: Microsoft took over BrightBytes, an education technology company that develops software for analyzing schools' teaching programs and students' learning productivity through the use of technologies. The acquisition provided DataSense into Microsoft’s suite of educational products which helped institutions and schools to better collect, manage, and explicitly control access to their data within Azure.
- Dec-2018: Altair Engineering completed the acquisition of Datawatch Corporation. The acquisition provided data intelligence with market-leading enterprise data preparation, predictive analytics, and visualization solutions that fueled Altair's business analytics.
- Oct-2018: Cloudera, Inc. merged with Hortonworks, Inc., a data software company. The merged created the world's leading next-generation data provider. Together, the companies established the industry standard for hybrid cloud data management, enhancing customer adoption, partner engagement, and community development.
- Jun-2017: Alteryx, Inc. acquired Yhat, Inc., a provider of an end-to-end data science platform for developing, deploying, and managing real-time decision APIs. The acquisition enhanced the Alteryx data analytics platform and builds a strategy to help organizations in empowering citizen data scientists and trained data scientists to rapidly deploy and manage advanced analytic models.
- Jan-2016: IBM acquired The Weather Company’s Product and Technology Businesses. The acquisition was aimed to launch the first joint product, a hyperlocal weather forecast at a 0.2-mile to 1.2-mile resolution for providing enterprise clients with short-term customized forecasts.
» Product Launches and Product Expansions:
- Oct-2020: Microsoft made enhancements to the Customer Data Platform (CDP). It introduced the engagement insights capability that allows a deeper understanding of customer behavior and intent with cross-channel analytics from their mobile apps, websites, and connected products. Microsoft modified its CDP which is capable of a deeper understanding of customer intent and behavior with cross-channel analytics from their websites, mobile apps, and connected products.
- Oct-2020: SAP unveiled the new Customer Data Platform at SAP Customer Experience. The platform enabled organizations in creating individual but anonymized 360-degree customer profiles using data from multiple sources within and outside of a company, including online sources and social channels.
- Sep-2020: Cloudera launched a suite of enterprise data cloud services known as analytic experiences. These services have been designed for data specialists like data engineers, analysts, and scientists. It includes Enterprise data cloud services that comprise of CDP Data Engineering, CDP Operational Database, and CDP Data Visualization.
- Jun-2020: Altair announced the software update release. The update expanded the number of solutions available for designers, engineers, data analysts, IT and HPC professionals, facility managers, and broadened the scope of the new user experience.
- Feb-2020: RapidMiner launched RapidMiner 9.6, which provides new and unique experiences. The RapidMiner 9.6 platform enables collaboration between coders, non-coding data scientists, and business users by combining automated data science, visual workflows, and coding as needed or preferred.
- Oct-2019: RapidMiner upgraded RapidMiner AI Cloud, a unified SaaS platform. This platform made it easy for teams to build, train, manage, and deploy predictive models in the cloud and provides a suite of applications for the entire analytics team.
- Sep-2019: Cloudera introduced the new Cloud-Native Machine Learning Service for Cloudera Data Platform. This service aimed to empower the AI-First Enterprise. The step-up in launching the Machine Learning focused on rapidly deploying new ML Workspaces or virtual machine learning environments for teams in a few clicks, providing self-service access to the shared data and tools required for end-to-end machine learning workflows, anywhere.
- Apr-2019: Google launched its AI platform. The platform has its focus on supporting Kubeflow, Google’s open-source platform, which enables users to build portable ML pipelines that can be run on-premises or on Google Cloud without significant code changes.
- Mar-2019: MathWorks announced the release of 2019a of MATLAB and Simulink. The release included new products and important enhancements for signal processing, artificial intelligence (AI), and static analysis, along with new capabilities and bug fixes across all product families. With R2019a, MathWorks enabled engineers for quickly and effectively extending their AI skills, whether it’s to develop controllers and decision-making systems using reinforcement learning, training deep learning models on NVIDIA DGX, and cloud platforms, or applying deep learning to 3-D data.
Scope of the Data Science Platform Market Analysis
- Platform (Without Services)
By Deployment Type
By Enterprise Size
- Large Enterprise
- Small & Medium Enterprise
- Marketing & Sales
- Customer Support
- Finance & Accounting
- Energy & Utilities
- Retail & eCommerce
- Government & Defense
- IT & Telecommunication
- North America
- Rest of North America
- Rest of Europe
- Asia Pacific
- South Korea
- Rest of Asia Pacific
- Saudi Arabia
- South Africa
- Rest of LAMEA
- IBM Corporation
- Microsoft Corporation
- Google, Inc.
- SAP SE
- Altair Engineering, Inc.
- Alteryx, Inc.
- Cloudera, Inc.
- The MathWorks, Inc.
- SAS Institute, Inc.
- RapidMiner, Inc.
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Data Science Platform Market Related Reports:
What would be the value of global data science platform market by 2026?
The data science platform is projected to reach USD 165.5 billion by 2026.
What are the key factors that drive data science platform industry?
There are several reason that cause high demand of this market one of them is adoption of cloud-based solutions and services.
Which segment shows big income share of the data science platform market in 2019?
The marketing and sales segment represented the biggest income share in 2019.
At what CAGR is the data science platform market estimate to grow in the forecast period?
The expected CAGR of data science platform market is 27% from 2020 to 2026.
Who are the leading players in data science platform market?
IBM Corporation, Microsoft Corporation, Google, Inc., SAP SE, Altair Engineering, Inc., Alteryx, Inc., Cloudera, Inc., The MathWorks, Inc., SAS Institute, Inc., and RapidMiner, Inc.