Data science platform is a packaged software application that provides the tools for the entire life cycle of a data science project. Data science platforms are indispensables tools for data scientists. It enables data exploration, model development, and model distribution. It facilitates data preparation and data visualization while providing a large-scale computing infrastructure. Data science platforms help users collaborate by providing a centralized platform. They serve as a one-stop shop for data modeling because data science platforms contain the APIs to allow for model production and testing with minimal outside engineering needs.
Increase in reliance on machine learning creates a need for data science platforms that fulfill needs in building, training, scaling, and deploying machine learning (ML) models. The proper platforms and technologies enable breakthroughs in data science. In addition, machine learning and artificial intelligence are driving innovations in data science and data management. The advancement of big data technology and importance of collecting and using data for decision making are anticipated to drive the market growth during the forecast period. However, high investment cost, data privacy & security, and reliability issues observed by the employees hamper the market growth. Moreover, adoption of cloud-based solutions & services and targeting untapped and emerging market for data science platforms are expected to provide ample growth opportunities for the market during forecast period.
Data science platform market is segmented on the basis of component, application, industry vertical, and region. On the basis of component, it is divided into platform and services. On the basis of application, it is divided into marketing & sales, logistics, finance and accounting, customer support, and others. According to the industry vertical, it is segmented into BFSI, IT & telecommunication, retail & E-Commerce, healthcare, transportation, manufacturing and others). Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The global data science platform market is dominated by key players such as Microsoft Corporation, IBM Corporation, SAS Institute, Inc., SAP SE, RapidMiner, Inc., Dataiku, Alteryx, Inc., FICO, The MathWorks, Inc., and Teradata.
Increase in reliance on machine learning creates a need for data science platforms that fulfill needs in building, training, scaling, and deploying machine learning (ML) models. The proper platforms and technologies enable breakthroughs in data science. In addition, machine learning and artificial intelligence are driving innovations in data science and data management. The advancement of big data technology and importance of collecting and using data for decision making are anticipated to drive the market growth during the forecast period. However, high investment cost, data privacy & security, and reliability issues observed by the employees hamper the market growth. Moreover, adoption of cloud-based solutions & services and targeting untapped and emerging market for data science platforms are expected to provide ample growth opportunities for the market during forecast period.
Data science platform market is segmented on the basis of component, application, industry vertical, and region. On the basis of component, it is divided into platform and services. On the basis of application, it is divided into marketing & sales, logistics, finance and accounting, customer support, and others. According to the industry vertical, it is segmented into BFSI, IT & telecommunication, retail & E-Commerce, healthcare, transportation, manufacturing and others). Region wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The global data science platform market is dominated by key players such as Microsoft Corporation, IBM Corporation, SAS Institute, Inc., SAP SE, RapidMiner, Inc., Dataiku, Alteryx, Inc., FICO, The MathWorks, Inc., and Teradata.
Key Benefits For Stakeholders
- The study provides an in-depth analysis of the Data science platform market along with current trends and future estimations to elucidate imminent investment pockets.
- Information about key drivers, restrains, and opportunities and their impact analysis on the market size is provided in the report.
- Porter’s five forces analysis illustrates the potency of buyers and suppliers operating in the industry.
- The quantitative analysis of Data science platform market for the period 2020-2030 is provided to determine the market potential.
Key Market Segments
By Component
- Platform
- Services
By Application
- Marketing Sales
- Logistics
- Finance and Accounting
- Customer Support
- Others
By Industry Vertical
- BFSI
- Retail and E-Commerce
- IT and Telecom
- Transportation
- Healthcare
- Manufacturing
- Others
By Region
- North America
- U.S.
- Canada
- Europe
- U.K.
- Germany
- France
- Spain
- Italy
- Rest of Europe
- Asia-Pacific
- China
- India
- Japan
- Australia
- South Korea
- Rest of Asia-Pacific
- LAMEA
- Latin America
- Middle East
- Africa
Key Market Players
- MICROSOFT CORPORATION
- SAS INSTITUTE INC.
- FAIR ISSAC CORPORATION (FICO)
- INTERNATIONAL BUSINESS MACHINES CORPORATION (IBM CORPORATION)
- SAP SE
- TERADATA CORPORATION
- ALTREYX, INC.
- DATAIKU SAS
- RAPIDMINER INC
- THE MATHWORKS INC
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Table of Contents
CHAPTER 1: INTRODUCTION
CHAPTER 2: EXECUTIVE SUMMARY
CHAPTER 3: MARKET OVERVIEW
CHAPTER 4: GLOBAL DATA SCIENCE PLATFORM MARKET, BY COMPONENT
CHAPTER 5: GLOBAL DATA SCIENCE PLATFORM MARKET, BY APPLICATION
CHAPTER 6: GLOBAL DATA SCIENCE PLATFORM MARKET, BY INDUSTRY VERTICAL
CHAPTER 7: GLOBAL DATA SCIENCE PLATFORM MARKET, BY REGION
CHAPTER 8: COMPANY LANDSCAPE
CHAPTER 9: COMPANY PROFILES
LIST OF TABLES
LIST OF FIGURES
Executive Summary
According to this report titled, 'Global Data Science Platform Market,' the global data science platform market was valued at $4.7 billion in 2020, and is estimated to reach $79.7 billion by 2030, growing at a CAGR of 33.6% from 2021 to 2030.The importance of collecting and using data for better decision making and advancements in big data technology drive the market growth. However, data security & high investment costs and reliability issues observed by the employees hamper the market growth. In addition, targeting untapped and emerging market for data science platforms and adoption of cloud-based solutions and services are expected to provide lucrative opportunities for market growth during forecast period.
On the basis of component, the platform segment dominated the data science platform market share in 2020 and is expected to maintain its dominance in the forecast period. This is due to the increase in adoption of data science platforms in small and medium enterprises (SMEs). Companies move toward digitization and automation, which accelerate big data and lead to more complex business processes. To deal with these complexities, companies need cutting-edge technologies that enable them to gain real-time insights across vast data pools. The data science platform helps them streamline business processes and gain new customers. However, the services segment is expected to witness highest growth rate during the forecast period.
As per the application, marketing & Sales segment dominated the global market in 2020. This is attributed to the fact that marketing and sales departments of the companies can get more insights into the buyer’s persona and spend by generating more Return on Investment. The data science platform is rapidly being used in marketing for channel optimization, lead targeting, customer segmentation, and advanced lead scoring.
However, customer support segment is expected to witness highest growth rate during the forecast period owing to the upsurge in usage of customer service analytics to collect and analyze customer feedback to discover valuable insights.
Region wise, North America dominated the data science platform market in 2020. Growth of the market in this region is attributed to several factors, such as rapid digitalization along with the surge in government funding on innovative technologies, increase in number of IoT devices, and growth in technical base.
The current estimation of 2030 is projected to be higher than pre-COVID-19 estimates. The outbreak of COVID-19 has caused a great deal of difficulties across the world. During the COVID-19 pandemic, Data science platform are playing a vital role in data management and smooth running of many sectors such as BFSI, Healthcare and Manufacturing.
The COVID-19 have positively impacted the growth of the market and COVID-19 will surely provide numerous opportunities for the market to grow in the forecasted period. These opportunities include a surge in demand for Data science platform in enterprises due to remote work initiatives, increase in healthcare applications, and introduction of innovative Data science platform solutions.
The advantages of data science platform have become more obvious during the COVID-19 pandemic. The overall lockdown has constrained organizations to move toward digitalization for the arrangement of work from home officers to their employee. The effect of the COVID-19 pandemic is altogether driving the interest for data science platforms as the main technology companies are integrating automation and intelligence into their organizations.
Key findings of the Study
- By component, in 2020 the platform segment dominated the Data science platform market size. However, the services segment is expected to exhibit significant growth during Data science platform market forecast period.
- By industry vertical, the BFSI generated the highest revenue in 2020 of Data science platform market share. However, the manufacturing segment is expected to exhibit significant growth during the forecast period.
- As per the application, marketing & Sales segment dominated the global market
- Region wise, the Data science platform industry was dominated by North America region. However, Asia-Pacific is expected to witness significant growth in the upcoming years.
- Some of the key Data science platform industry players profiled in the report include Microsoft Corporation, IBM Corporation, SAS Institute, Inc., SAP SE, RapidMiner, Inc., Dataiku, Alteryx, Inc., FICO, The MathWorks, Inc., and Teradata. This study includes market trends, Data science platform market analysis, and future estimations to determine the imminent investment pockets.
Companies Mentioned
- MICROSOFT CORPORATION
- SAS INSTITUTE INC.
- FAIR ISSAC CORPORATION (FICO)
- INTERNATIONAL BUSINESS MACHINES CORPORATION (IBM CORPORATION)
- SAP SE
- TERADATA CORPORATION
- ALTREYX, INC.
- DATAIKU SAS
- RAPIDMINER INC
- THE MATHWORKS INC
Methodology
The analyst offers exhaustive research and analysis based on a wide variety of factual inputs, which largely include interviews with industry participants, reliable statistics, and regional intelligence. The in-house industry experts play an instrumental role in designing analytic tools and models, tailored to the requirements of a particular industry segment. The primary research efforts include reaching out participants through mail, tele-conversations, referrals, professional networks, and face-to-face interactions.
They are also in professional corporate relations with various companies that allow them greater flexibility for reaching out to industry participants and commentators for interviews and discussions.
They also refer to a broad array of industry sources for their secondary research, which typically include; however, not limited to:
- Company SEC filings, annual reports, company websites, broker & financial reports, and investor presentations for competitive scenario and shape of the industry
- Scientific and technical writings for product information and related preemptions
- Regional government and statistical databases for macro analysis
- Authentic news articles and other related releases for market evaluation
- Internal and external proprietary databases, key market indicators, and relevant press releases for market estimates and forecast
Furthermore, the accuracy of the data will be analyzed and validated by conducting additional primaries with various industry experts and KOLs. They also provide robust post-sales support to clients.
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