Press release
Data Science Platform Market to Significant Growth Foreseen by 2017 - 2025
Data science platform provides real-time data streaming and more advanced data pipelines which will support redefine big data into different categories such as actionable and fast data. A massive increase in data volume is the driving force for the data science platform. This movement of Data volume will continue to evolve shortly.
Data science platform aid to facilitate a high level of association across data scientists, business analysts, data engineers, and developers in different fields of business. Data Science platforms help the organizations to prepare data, build models and operationalize analytics.
Data Science Platform: Market Dynamics
The increasing demand for public cloud, adoption of artificial intelligence, the explosive growth of 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. Key IT Trends in enterprises are an adoption of big data technology, security, and governance, IT centralization, open standard, and libraries, etc. are adapted to data science platform to provide efficient enterprise solutions across various sectors.
The emergence of unified, multidisciplinary cloud-based development environments assist the data scientist to enhance data science skills, and collaborate the machine learning and analytics into the core business. Data science platforms are used as an approach in order to find concealed bits of knowledge from large measures of classified and unstructured information, utilizing techniques such as insights, machine learning, predictive analytics, and data mining. This area consists of different branches which help to identify changes in the way organizations solve the issues and gain competitive advantage. The growth of analytics apps and APIs which are accessed on browser and device is the recent trend in data service platform market.
A sample of this report is available upon request @ https://www.persistencemarketresearch.com/samples/14752
Data explosion, lack of domain expertise and lack of analytical capabilities are few challenges in the data science platform market.
Data Science Platform: Market Segmentation
Based on the application data science platform market is segmented into healthcare and life science, automotive, manufacturing, banking, financial service and insurance (BFSI), information technology and telecommunications, media and entertainment, retail and consumer goods, energy and utilities, transportation and logistics and government. Based on business function, it is segmented into marketing, logistics, operations and Human resources. Data science platform market is segmented based on deployment type such as on premises and on-demand.
Segmentation Overview
Based on Application
Healthcare and life science
Information technology and telecommunication
Automotive
Manufacturing
BFSI
Media and entertainment
Retail and consumer goods
Energy and utilities
Transportation and logistics
Government
Based on deployment type
On-premises
Cloud-based
Based on Business function
Marketing
Logistics
Operations
Human Resources
Data Science Platform: Competition Landscape
Some of the prominent players offering the data science platform are Cloudera Inc., RapidMiner, Inc., Domino Data Lab, Inc., Kaggle Inc., Yhat Inc., Micropole S.A., Dataiku SAS, Continuum Analytics, Inc., C&F Insight technology solutions, Civis Analytics, Inc., and IBM Corporation.
Data Science Platform: Key Developments
In 2016, IBM Corporation launched IBM Watson Data Platform, a cloud-based data ingestion engine in order to enhance its data analytics platform.
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Persistence Market Research (PMR) is a third-platform research firm. Our research model is a unique collaboration of data analytics and market research methodology to help businesses achieve optimal performance. To support companies in overcoming complex business challenges, we follow a multi-disciplinary approach. At PMR, we unite various data streams from multi-dimensional sources. By deploying real-time data collection, big data, and customer experience analytics, we deliver business intelligence for organizations of all sizes.
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