Europe 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 Country, Industry Analysis and Forecast, 2020 - 2026
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The Europe Data Science Platform Market would witness market growth of 26% CAGR during the forecast period (2020-2026). A data science platform can be considered as a system of the complete life cycle of a data science venture. The data science platform contains all the instruments needed for executing the lifecycle of the data science venture spanning across various phases, for example, data ideation, integration and implementation, model development, and model installation. Data science platform assists companies to upgrade their analysis by helping them run, track, reproduce, share, and deploy analytical models quicker. Commonly, every one of these tasks needs much engineering effort, and is hard to assemble and maintain analytics models. Data science platforms provide data science groups an advantage in serious competition to use analytics successfully.
The worldwide data science platform market is being boosted by factors, for example, a worldwide rapid progression in big data innovations, demand for big data analysis to get deeper insights into user purchasing behaviors, and the requirement for ease of using technological techniques to drive business viability. Data science platforms help to encourage a significant level of relationship across data researchers, business experts, data specialists, and developers in various fields of business. Data Science platforms assist the companies to prepare data, manufacturing models, and operationalize analytics.
The data science platform includes a set of new-age innovations and architecture that are uncommonly designed as a system of the complete data science project. It comprises of instruments that are needed to execute the life cycle of the data science project, which comprises various phases, for example, data ideation, integration & exploration; model development, and model deployment. In the current situation, it has become a significant investment decision that has altogether added to the development of the smart and digital industry.
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 countries, the market is segmented into Germany, UK, France, Russia, Spain, Italy, and Rest of Europe.
The market research report covers theanalysis 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.
Scope of the Europe 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
- Rest of Europe
- 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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