Press release
Global Data Science Platform market:Competitive Landscape & Key Player Tactics|Microsoft, IBM, Google
The latest report up for sale by QY Research demonstrates that the global Data Science Platform market is likely to garner a great pace in the coming years. Analysts have scrutinized the market drivers, confinements, risks, and openings present in the overall market. The report shows course the market is expected to take in the coming years along with its estimations. The careful examination is aimed at understanding of the course of the market.
Global Data Science Platform Market: Segmentation
The global market for Data Science Platform is segmented on the basis of product, type, services, and technology. All of these segments have been studied individually. The detailed investigation allows assessment of the factors influencing the market. Experts have analyzed the nature of development, investments in research and development, changing consumption patterns, and a growing number of applications. In addition, analysts have also evaluated the changing economics around the market that are likely affecting its course.
Get a PDF brochure of this report: https://www.qyresearch.com/sample-form/form/3327261/global-and-china-data-science-platform-market
Global Data Science Platform Market Competition by Players :
Microsoft, IBM, Google, Wolfram, Datarobot, Cloudera, Rapidminer, Domino Data Lab, Dataiku, Alteryx, Continuum Analytics, Bridgei2i Analytics, Datarpm, Rexer Analytics, Feature Labs
Global Data Science Platform Sales and Revenue by Product Type Segments
On-Premises, On-Demand Data Science Platform
Global Data Science Platform Sales and Revenue by Application Segments
Marketing, Sales, Logistics, Risk, Customer Support, Human Resources, Operations
Global Data Science Platform Market: Regional Segmentation
The market is also segmented on the basis of geography. This segmentation allows the readers to get a holistic understanding of the market. It highlights the changing nature of the economies within the geographies that are influencing the global Data Science Platform market. Some of the geographical regions studied in the overall market are as follows:
The Middle East and Africa (GCC Countries and Egypt)
North America (the United States, Mexico, and Canada)
South America (Brazil etc.)
Europe (Turkey, Germany, Russia UK, Italy, France, etc.)
Asia-Pacific (Vietnam, China, Malaysia, Japan, Philippines, Korea, Thailand, India, Indonesia, and Australia)
Global Data Science Platform Market: Research Methodology
The analysts at QY Research have used fundamental investigative approaches for a thorough examination of the global Data Science Platform market. The collected information has been closely evaluated to understand subtleties accurately. Moreover, data has been gathered from journals and market research experts to put together a document that sheds light on the ever-changing nature of market dynamics in an unbiased way.
Global Data Science Platform Market: Competitive Rivalry
Analysts have also discussed the nature of the competition present in the global Data Science Platform market. Companies have been discussed at great length to ascertain the leading ones and note the emerging ones. The report also mentions the strategic initiatives taken by these companies to get ahead of the game. Analysts look at potential mergers and acquisitions that are likely to define the progress of the market in the coming years.
Enquire for customization in Report @ https://www.qyresearch.com/customize-request/form/3327261/global-and-china-data-science-platform-market
TOC :
1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Data Science Platform Market Size Growth Rate by Type: 2016 VS 2021 VS 2027
1.2.2 On-Premises
1.2.3 On-Demand
1.3 Market by Application
1.3.1 Global Data Science Platform Market Share by Application: 2016 VS 2021 VS 2027
1.3.2 Marketing
1.3.3 Sales
1.3.4 Logistics
1.3.5 Risk
1.3.6 Customer Support
1.3.7 Human Resources
1.3.8 Operations
1.4 Study Objectives
1.5 Years Considered 2 Global Growth Trends
2.1 Global Data Science Platform Market Perspective (2016-2027)
2.2 Data Science Platform Growth Trends by Regions
2.2.1 Data Science Platform Market Size by Regions: 2016 VS 2021 VS 2027
2.2.2 Data Science Platform Historic Market Share by Regions (2016-2021)
2.2.3 Data Science Platform Forecasted Market Size by Regions (2022-2027)
2.3 Data Science Platform Industry Dynamic
2.3.1 Data Science Platform Market Trends
2.3.2 Data Science Platform Market Drivers
2.3.3 Data Science Platform Market Challenges
2.3.4 Data Science Platform Market Restraints 3 Competition Landscape by Key Players
3.1 Global Top Data Science Platform Players by Revenue
3.1.1 Global Top Data Science Platform Players by Revenue (2016-2021)
3.1.2 Global Data Science Platform Revenue Market Share by Players (2016-2021)
3.2 Global Data Science Platform Market Share by Company Type (Tier 1, Tier 2 and Tier 3)
3.3 Players Covered: Ranking by Data Science Platform Revenue
3.4 Global Data Science Platform Market Concentration Ratio
3.4.1 Global Data Science Platform Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Data Science Platform Revenue in 2020
3.5 Data Science Platform Key Players Head office and Area Served
3.6 Key Players Data Science Platform Product Solution and Service
3.7 Date of Enter into Data Science Platform Market
3.8 Mergers & Acquisitions, Expansion Plans 4 Data Science Platform Breakdown Data by Type
4.1 Global Data Science Platform Historic Market Size by Type (2016-2021)
4.2 Global Data Science Platform Forecasted Market Size by Type (2022-2027) 5 Data Science Platform Breakdown Data by Application
5.1 Global Data Science Platform Historic Market Size by Application (2016-2021)
5.2 Global Data Science Platform Forecasted Market Size by Application (2022-2027) 6 North America
6.1 North America Data Science Platform Market Size (2016-2027)
6.2 North America Data Science Platform Market Size by Type
6.2.1 North America Data Science Platform Market Size by Type (2016-2021)
6.2.2 North America Data Science Platform Market Size by Type (2022-2027)
6.2.3 North America Data Science Platform Market Size by Type (2016-2027)
6.3 North America Data Science Platform Market Size by Application
6.3.1 North America Data Science Platform Market Size by Application (2016-2021)
6.3.2 North America Data Science Platform Market Size by Application (2022-2027)
6.3.3 North America Data Science Platform Market Size by Application (2016-2027)
6.4 North America Data Science Platform Market Size by Country
6.4.1 North America Data Science Platform Market Size by Country (2016-2021)
6.4.2 North America Data Science Platform Market Size by Country (2022-2027)
6.4.3 United States
6.4.4 Canada 7 Europe
7.1 Europe Data Science Platform Market Size (2016-2027)
7.2 Europe Data Science Platform Market Size by Type
7.2.1 Europe Data Science Platform Market Size by Type (2016-2021)
7.2.2 Europe Data Science Platform Market Size by Type (2022-2027)
7.2.3 Europe Data Science Platform Market Size by Type (2016-2027)
7.3 Europe Data Science Platform Market Size by Application
7.3.1 Europe Data Science Platform Market Size by Application (2016-2021)
7.3.2 Europe Data Science Platform Market Size by Application (2022-2027)
7.3.3 Europe Data Science Platform Market Size by Application (2016-2027)
7.4 Europe Data Science Platform Market Size by Country
7.4.1 Europe Data Science Platform Market Size by Country (2016-2021)
7.4.2 Europe Data Science Platform Market Size by Country (2022-2027)
7.4.3 Germany
7.4.4 France
7.4.5 U.K.
7.4.6 Italy
7.4.7 Russia
7.4.8 Nordic 8 Asia-Pacific
8.1 Asia-Pacific Data Science Platform Market Size (2016-2027)
8.2 Asia-Pacific Data Science Platform Market Size by Type
8.2.1 Asia-Pacific Data Science Platform Market Size by Type (2016-2021)
8.2.2 Asia-Pacific Data Science Platform Market Size by Type (2022-2027)
8.2.3 Asia-Pacific Data Science Platform Market Size by Type (2016-2027)
8.3 Asia-Pacific Data Science Platform Market Size by Application
8.3.1 Asia-Pacific Data Science Platform Market Size by Application (2016-2021)
8.3.2 Asia-Pacific Data Science Platform Market Size by Application (2022-2027)
8.3.3 Asia-Pacific Data Science Platform Market Size by Application (2016-2027)
8.4 Asia-Pacific Data Science Platform Market Size by Region
8.4.1 Asia-Pacific Data Science Platform Market Size by Region (2016-2021)
8.4.2 Asia-Pacific Data Science Platform Market Size by Region (2022-2027)
8.4.3 China
8.4.4 Japan
8.4.5 South Korea
8.4.6 Southeast Asia
8.4.7 India
8.4.8 Australia 9 Latin America
9.1 Latin America Data Science Platform Market Size (2016-2027)
9.2 Latin America Data Science Platform Market Size by Type
9.2.1 Latin America Data Science Platform Market Size by Type (2016-2021)
9.2.2 Latin America Data Science Platform Market Size by Type (2022-2027)
9.2.3 Latin America Data Science Platform Market Size by Type (2016-2027)
9.3 Latin America Data Science Platform Market Size by Application
9.3.1 Latin America Data Science Platform Market Size by Application (2016-2021)
9.3.2 Latin America Data Science Platform Market Size by Application (2022-2027)
9.3.3 Latin America Data Science Platform Market Size by Application (2016-2027)
9.4 Latin America Data Science Platform Market Size by Country
9.4.1 Latin America Data Science Platform Market Size by Country (2016-2021)
9.4.2 Latin America Data Science Platform Market Size by Country (2022-2027)
9.4.3 Mexico
9.4.4 Brazil 10 Middle East & Africa
10.1 Middle East & Africa Data Science Platform Market Size (2016-2027)
10.2 Middle East & Africa Data Science Platform Market Size by Type
10.2.1 Middle East & Africa Data Science Platform Market Size by Type (2016-2021)
10.2.2 Middle East & Africa Data Science Platform Market Size by Type (2022-2027)
10.2.3 Middle East & Africa Data Science Platform Market Size by Type (2016-2027)
10.3 Middle East & Africa Data Science Platform Market Size by Application
10.3.1 Middle East & Africa Data Science Platform Market Size by Application (2016-2021)
10.3.2 Middle East & Africa Data Science Platform Market Size by Application (2022-2027)
10.3.3 Middle East & Africa Data Science Platform Market Size by Application (2016-2027)
10.4 Middle East & Africa Data Science Platform Market Size by Country
10.4.1 Middle East & Africa Data Science Platform Market Size by Country (2016-2021)
10.4.2 Middle East & Africa Data Science Platform Market Size by Country (2022-2027)
10.4.3 Turkey
10.4.4 Saudi Arabia
10.4.5 UAE 11 Key Players Profiles
11.1 Microsoft
11.1.1 Microsoft Company Details
11.1.2 Microsoft Business Overview
11.1.3 Microsoft Data Science Platform Introduction
11.1.4 Microsoft Revenue in Data Science Platform Business (2016-2021)
11.1.5 Microsoft Recent Development
11.2 IBM
11.2.1 IBM Company Details
11.2.2 IBM Business Overview
11.2.3 IBM Data Science Platform Introduction
11.2.4 IBM Revenue in Data Science Platform Business (2016-2021)
11.2.5 IBM Recent Development
11.3 Google
11.3.1 Google Company Details
11.3.2 Google Business Overview
11.3.3 Google Data Science Platform Introduction
11.3.4 Google Revenue in Data Science Platform Business (2016-2021)
11.3.5 Google Recent Development
11.4 Wolfram
11.4.1 Wolfram Company Details
11.4.2 Wolfram Business Overview
11.4.3 Wolfram Data Science Platform Introduction
11.4.4 Wolfram Revenue in Data Science Platform Business (2016-2021)
11.4.5 Wolfram Recent Development
11.5 Datarobot
11.5.1 Datarobot Company Details
11.5.2 Datarobot Business Overview
11.5.3 Datarobot Data Science Platform Introduction
11.5.4 Datarobot Revenue in Data Science Platform Business (2016-2021)
11.5.5 Datarobot Recent Development
11.6 Cloudera
11.6.1 Cloudera Company Details
11.6.2 Cloudera Business Overview
11.6.3 Cloudera Data Science Platform Introduction
11.6.4 Cloudera Revenue in Data Science Platform Business (2016-2021)
11.6.5 Cloudera Recent Development
11.7 Rapidminer
11.7.1 Rapidminer Company Details
11.7.2 Rapidminer Business Overview
11.7.3 Rapidminer Data Science Platform Introduction
11.7.4 Rapidminer Revenue in Data Science Platform Business (2016-2021)
11.7.5 Rapidminer Recent Development
11.8 Domino Data Lab
11.8.1 Domino Data Lab Company Details
11.8.2 Domino Data Lab Business Overview
11.8.3 Domino Data Lab Data Science Platform Introduction
11.8.4 Domino Data Lab Revenue in Data Science Platform Business (2016-2021)
11.8.5 Domino Data Lab Recent Development
11.9 Dataiku
11.9.1 Dataiku Company Details
11.9.2 Dataiku Business Overview
11.9.3 Dataiku Data Science Platform Introduction
11.9.4 Dataiku Revenue in Data Science Platform Business (2016-2021)
11.9.5 Dataiku Recent Development
11.10 Alteryx
11.10.1 Alteryx Company Details
11.10.2 Alteryx Business Overview
11.10.3 Alteryx Data Science Platform Introduction
11.10.4 Alteryx Revenue in Data Science Platform Business (2016-2021)
11.10.5 Alteryx Recent Development
11.11 Continuum Analytics
11.11.1 Continuum Analytics Company Details
11.11.2 Continuum Analytics Business Overview
11.11.3 Continuum Analytics Data Science Platform Introduction
11.11.4 Continuum Analytics Revenue in Data Science Platform Business (2016-2021)
11.11.5 Continuum Analytics Recent Development
11.12 Bridgei2i Analytics
11.12.1 Bridgei2i Analytics Company Details
11.12.2 Bridgei2i Analytics Business Overview
11.12.3 Bridgei2i Analytics Data Science Platform Introduction
11.12.4 Bridgei2i Analytics Revenue in Data Science Platform Business (2016-2021)
11.12.5 Bridgei2i Analytics Recent Development
11.13 Datarpm
11.13.1 Datarpm Company Details
11.13.2 Datarpm Business Overview
11.13.3 Datarpm Data Science Platform Introduction
11.13.4 Datarpm Revenue in Data Science Platform Business (2016-2021)
11.13.5 Datarpm Recent Development
11.14 Rexer Analytics
11.14.1 Rexer Analytics Company Details
11.14.2 Rexer Analytics Business Overview
11.14.3 Rexer Analytics Data Science Platform Introduction
11.14.4 Rexer Analytics Revenue in Data Science Platform Business (2016-2021)
11.14.5 Rexer Analytics Recent Development
11.15 Feature Labs
11.15.1 Feature Labs Company Details
11.15.2 Feature Labs Business Overview
11.15.3 Feature Labs Data Science Platform Introduction
11.15.4 Feature Labs Revenue in Data Science Platform Business (2016-2021)
11.15.5 Feature Labs Recent Development 12 Analyst's Viewpoints/Conclusions 13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details
Contact US:
QY Research, INC.
17890 Castleton,
Suite 218,
City of industry, CA – 91748
USA: +1 626 295 2442
Email: enquiry@qyresearch.com
Web: http://www.qyresearch.com
About Us
In QY Research we give immense importance to the needs of our clients and assist them in offering appropriate solutions to innovate their business strategies. What we do is basically analyze the client's history and then create an analytical model to resolve their problems. Our client-centered services also offer insights on customer profiling, target market analysis, and behavioral analysis to meet customers' needs.
This release was published on openPR.
Permanent link to this press release:
Copy
Please set a link in the press area of your homepage to this press release on openPR. openPR disclaims liability for any content contained in this release.
You can edit or delete your press release Global Data Science Platform market:Competitive Landscape & Key Player Tactics|Microsoft, IBM, Google here
News-ID: 2335801 • Views: …
More Releases from QY Research, Inc
Global High Pressure Commercial Toilet Market Insights - Industry Share, Sales P …
High Pressure Commercial Toilet also means pressure-flushing toilets. Pressure-flushing toilets are especially common in cities in the U.S. The ceramic tank is not used as a water tank. It holds a plastic pressure vessel of maybe one-third to one-half the ceramic tank"s volume. That pressure tank contains a sealed air bladder. When the tank is filled from the water supply line, the tank fills with water until the air bladder…
Global Twin-Screw Pumps Market Insights - Industry Share, Sales Projections, and …
Twin-Screw Pumps is a displacement pump consisting of a casing containing two parallel screws with intermeshing threads fitted to prevent backward movement of fluid
The global Twin-Screw Pumps market was valued at US$ 503 million in 2023 and is anticipated to reach US$ 629 million by 2030, witnessing a CAGR of 3.3% during the forecast period 2024-2030.
The top five global producers of twin-screw pumps are Colfax, ITT Bornemann, Flowserve, SPX Flow…
Global Strain Gauge Sensors Market Insights - Industry Share, Sales Projections, …
A strain gauge (or strain gage) is a sensor whose resistance varies with applied force; it converts force, pressure, tension, weight, etc., into a change in electrical resistance which can then be measured. When external forces are applied to a stationary object, stress and strain are the result. Stress is defined as the object"s internal Strain Gauge forces, and strain is defined as the displacement and deformation that occur.
The global…
Global Automatic Soap Dispensers Market Insights - Industry Share, Sales Project …
Automatic soap dispensers (also known as touchless or no-touch soap dispensers) dispense a controlled amount of soap solution (or a similar liquid such as a hand sanitizer). They are often used in conjunction with automatic faucets in public restrooms. They function to conserve the amount of soap used and stem infectious disease transmission.
The global Automatic Soap Dispensers market was valued at US$ million in 2023 and is anticipated to reach…
More Releases for Data
Data Catalog Market: Serving Data Consumers
Data Catalog Market size was valued at US$ 801.10 Mn. in 2022 and the total revenue is expected to grow at a CAGR of 23.2% from 2023 to 2029, reaching nearly US$ 3451.16 Mn.
Data Catalog Market Report Scope and Research Methodology
The Data Catalog Market is poised to reach a valuation of US$ 3451.16 million by 2029. A data catalog serves as an organized inventory of an organization's data assets, leveraging…
Big Data Security: Increasing Data Volume and Data Velocity
Big data security is a term used to describe the security of data that is too large or complex to be managed using traditional security methods. Big data security is a growing concern for organizations as the amount of data generated continues to increase. There are a number of challenges associated with securing big data, including the need to store and process data in a secure manner, the need to…
HOW TO TRANSFORM BIG DATA TO SMART DATA USING DATA ENGINEERING?
We are at the cross-roads of a universe that is composed of actors, entities and use-cases; along with the associated data relationships across zillions of business scenarios. Organizations must derive the most out of data, and modern AI platforms can help businesses in this direction. These help ideally turn Big Data into plug-and-play pieces of information that are being widely known as Smart Data.
Specialized components backed up by AI and…
Test Data Management (TDM) Market - test data profiling, test data planning, tes …
The report categorizes the global Test Data Management (TDM) market by top players/brands, region, type, end user, market status, competition landscape, market share, growth rate, future trends, market drivers, opportunities and challenges, sales channels and distributors.
This report studies the global market size of Test Data Management (TDM) in key regions like North America, Europe, Asia Pacific, Central & South America and Middle East & Africa, focuses on the consumption…
Data Prep Market Report 2018: Segmentation by Platform (Self-Service Data Prep, …
Global Data Prep market research report provides company profile for Alteryx, Inc. (U.S.), Informatica (U.S.), International Business Corporation (U.S.), TIBCO Software, Inc. (U.S.), Microsoft Corporation (U.S.), SAS Institute (U.S.), Datawatch Corporation (U.S.), Tableau Software, Inc. (U.S.) and Others.
This market study includes data about consumer perspective, comprehensive analysis, statistics, market share, company performances (Stocks), historical analysis 2012 to 2017, market forecast 2018 to 2025 in terms of volume, revenue, YOY…
Long Term Data Retention Solutions Market - The Increasing Demand For Big Data W …
Data retention is a technique to store the database of the organization for the future. An organization may retain data for several different reasons. One of the reasons is to act in accordance with state and federal regulations, i.e. information that may be considered old or irrelevant for internal use may need to be retained to comply with the laws of a particular jurisdiction or industry. Another reason is to…
