Global Data Science Platform Market size was valued US$ XX Bn. in 2019 and the total revenue is expected to grow at XX% from 2020 to 2027, reaching nearly US$ XX Bn.

The report study has analyzed the revenue impact of COVID -19 pandemic on the sales revenue of market leaders, market followers, and market disrupters in the report, and the same is reflected in our analysis.

Definition:

A data science platform is a software hub around which all data science work takes place. That work usually includes integrating and exploring data from various sources, coding and building models that influence that data, organizing those models into production, and serving up results, whether that is through model-powered applications or reports.
These platforms are attracting the interest of organizations looking for enhancing business effectiveness and reducing human involvement. Thus, the adoption of such data-driven solutions is supporting the growth of the data science platform market. Data science platform helps to facilitate a high level of association across data scientists, business analysts, data engineers, and developers in different fields of business.

Market Dynamics:

The increasing demand for public cloud, adoption of artificial intelligence, the explosive growth of the Internet of things (IoT) applications and machine learning, revolution, and rise in demand of big data, etc. are the factor that are expected to drive the demand of data science platform market. The growth of analytics apps and APIs which are accessed on browser and device is the recent trend in the data service platform market.

The key impacting factors of the data science platform market include data explosion, the realization of the importance of data science by organizations, an increase in data collection & analysis from mobile devices, the advancement of big data technologies, growing concern of data security & protection, and high initial investments. These factors have significantly contributed to the growth of the data science platform market and are expected to impact market growth during the forecast period. The revenue of the global data science platform market is projected to grow by 7.4 times from 2019 to 2027 due to increasing expenditure on data science solutions and services. March 2018 - IBM Corporation announced a new cloud offering called Cloud Private Data that’s designed to help organizations utilize data science and machine learning techniques to generate insight from data, and then engineer AI products that put those insights into the use.

According to a report by Data Science Central, only 22% of companies are engaged in data science work. Data science is moving from the edge to the core of the business platforms, simplifying the use of interactive apps and application program interfaces to operationalize outcomes, and authorize users. It helps the organizations to prepare data, build models, and operationalize analytics.

Global Data Science Platform Market Drivers & Restraints:

Data Science Platform Market is opening vast possibilities for learning unobserved consumer purchasing patterns. These patterns enable organizations to comprehend key insights to help their business work efficiently, target potential customers, and offer better services. Furthermore, companies are adopting business analytics solutions that can provide effective outcomes from a large set of data, which, in turn, is boosting the growth of the data science platform market. The Data science platform industry has created the opportunity to transform into all sectors. There are many untapped markets such as the telecom industry, video analysis, etc., which has a promising future. Emerging markets such as Latin America, the Middle East, and Africa are expected to present significant growth opportunities for prominent players. Along with this data science platform, there is an opportunity of growth for other technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), machine learning, etc.
Data explosion, lack of domain expertise, and lack of analytical capabilities are few challenges in the data science platform market.

Market Segmentation:

Healthcare Sector to dominate the market over the Forecast Period.

Data science is also used for improving diagnostic accuracy and efficiency. Deep learning is being used to read imaging data such as x-rays, CT scans, and analyze it to reduce diagnostic failure rates. Being able to collect, structure, and process a high volume of data and further make sense of it, to gain a deeper understanding of the human body is the critical objective for thousands of data scientists and machine learning experts all over the world.

Using smart devices, such as scales and pedometers, personal health coaches are provided with an opportunity to gain more profound insights into the patient’s health and adjust the schedules along the way. Furthermore, the self-learning algorithm is continually improved as it sources more patient data from the system and integrates it in the data science platform.

Regional Analysis:

North America has the largest market size in 2018. North America market is predicted to grow at a CAGR of 30.1% by generating a revenue of $80.3 billion by 2027. The presence of a large number of multinational companies and rising use of data with the help of analytical tools in these companies give a boost to the market in this region. Asia-Pacific region is predicted to grow at a CAGR of 31.9% by generating a revenue of $48.0 billion by 2027. Asia-Pacific is accounted to have the highest growth due to increasing investments by companies and the increased use of artificial intelligence, cloud, and machine learning.

Key Development:

• In July 2019, Microsoft released Microsoft Machine Learning Server 9.4. This platform provides Python function libraries and R for ML and data science. It also contains updates for R and Python engines with additional Spark 2.4 and CDH 6.1 support.

• In August 2019, IBM announced IBM Data Science and Business Analytics Platform V1.3. The platform includes IBM Decision Optimization for private cloud, IBM SPSS Modeler, and IBM Planning Analytics Advanced that was previously called IBM Performance Management Advanced. The new platform would help data scientists and analysts in understanding, analyzing, and visualizing information.

• In April 2019, Google launched an AI platform. This platform will make the development of ML projects easier. It has an integrated toolchain that would assist in building and running ML applications. With this launch, Google’s AI technologies such as TensorFlow Extended (TFX), TensorFlow, and Tensor Processing Units (TPUs) would be easily accessible.

The objective of the report is to present a comprehensive analysis of the Global Data Science Platform Market including all the stakeholders of the industry. The past and current status of the industry with forecasted market size and trends are presented in the report with the analysis of complicated data in simple language. The report covers all the aspects of the industry with a dedicated study of key players that includes market leaders, followers, and new entrants. PORTER, SVOR, PESTEL analysis with the potential impact of micro-economic factors of the market has been presented in the report. External as well as internal factors that are supposed to affect the business positively or negatively have been analyzed, which will give a clear futuristic view of the industry to the decision-makers.

The report also helps in understanding Global Data Science Platform Market dynamics, structure by analyzing the market segments and projects the Global Data Science Platform Market size. Clear representation of competitive analysis of key players by Application, price, financial position, Product portfolio, growth strategies, and regional presence in the Global Data Science Platform Market make the report investor’s guide.

https://www.maximizemarketresearch.com/market-report/global-data-science-platform-market/66745/


Scope of the Global Data Science Platform Market

Global Data Science Platform Market, by deployment modes

• Cloud
• On-premises
Global Data Science Platform Market, by organization size

• Small and Medium-sized Enterprises (SMEs)
• Large Enterprises
Global Data Science Platform Market, by type

• Solutions
• Services
Global Data Science Platform Market, by End User

• BFSI
• Telecommunication
• Transportation and Logistics
• Healthcare
• Manufacturing
• Others (retail, education, government, energy, and utilities)
Global Data Science Platform Market, by Region

• Asia Pacific
• North America
• Europe
• Latin America
• Middle East Africa
Key players operating in Global Data Science Platform Market

• Microsoft Corporation
• IBM Corporation
• SAS Institute, Inc.
• SAP SE
• RapidMiner, Inc.
• Dataiku SAS
• Alteryx, Inc
• Fair Issac Corporation (FICO)
• MathWorks, Inc
• Teradata, Inc.