+353-1-416-8900REST OF WORLD
+44-20-3973-8888REST OF WORLD
1-917-300-0470EAST COAST U.S
1-800-526-8630U.S. (TOLL FREE)

Data Science Platform Market with COVID-19 Impact Analysis by Component (Platform & Services), Business Function (Marketing, Sales, Logistics, & Customer Support), Deployment Mode, Organization Size, Industry Vertical & Region - Global Forecast to 2026

  • PDF Icon

    Report

  • 351 Pages
  • March 2022
  • Region: Global
  • Markets and Markets
  • ID: 4988889

Increased Digitalization and Emerging Technologies, Such as Big Data, Ml, Analytics, Iot, and Ai, to Drive the Market Growth

The global Data Science Platform market is projected to grow from USD 95.3 billion in 2021 to USD 322.9 billion in 2026, at a Compound Annual Growth Rate (CAGR) of 27.64% during the forecast period. The Data Science Platform industry is driven by Astonishing growth of big data, however, Rising in adoption of cloud-based solutions, Rising application of the data science platform in various industries and Growing need to extract in-depth insights from voluminous data to gain competitive advantage.

Based on Component, the service segment is expected to grow at a higher CAGR during the forecast period

The service segment of the Data Science Platform market is further segmented into professional services (consulting, support and maintenance, and deployment and integration) and managed services. This section discusses each service subsegment's market size and growth rate based on type (for selected subsegments) and region.

Based on deployment mode, on-premises segment is segmented to account for a larger market size during the forecast period

Most enterprises mostly in heavily regulated industry verticals, such as BFSI, healthcare and life sciences, and manufacturing, opt for the on-premises deployment model of the data science platform. Large enterprises with sufficient IT resources are expected to opt for the on-premises deployment model. On-premises is the most reliable deployment mode, which an enterprise can rely on for the high level of control and security. Enterprises need to purchase the license or a copy to deploy the cloud-based platform. If an organization uses on-premises storage, they might also need to have IT staff to maintain and manage servers.

Based on business function, Finance and Accounting segment to grow at a higher CAGR during the forecast period

Financial services firms and banks, for example, use financial data science: Forward-thinking banks and FinTech’s improve customer service by evaluating transactional and behavioral data using various data science methods. Data science is already being used by some of the world's largest banks to acquire insights from previous customer purchases, engagements, and accounts that are most relevant to them. Investing items, insurance coverage, bank accounts, and mortgages are now the most common notices they receive. Data science is also providing insights into how well a product sells or to whom it sells, allowing financial services organizations and banks to build consumer products, policies, and investment instruments that will sell well in the future.

Based on organization size, large enterprise segment to account for a larger market size during the forecast period

Most Large enterprises considered in the report are organizations with an employee size of more than or equal to 1,000. The adoption of the data science platform among large enterprises is high due to the ever-increasing adoption of the cloud, and the trend is expected to continue during the forecast period. Large enterprises accumulate huge chunks of data that can be attributed to the widespread client base. In large enterprises, data plays a major role in evaluating the overall performance of organizations. Large enterprises are leveraging the data science platform coming from various sources, for instance, social media feeds or sensors and cameras, each record needs to be processed in a way that preserves its relation to other data and sequence in time.

APAC is expected to grow at a higher CAGR during the forecast period

Asia Pacific (APAC) has continually presented lucrative market opportunities for Data Science Platform Solutions and service providers with a notable increase in Data Science Platform across its developed and emerging countries., Japan, China, and India have displayed ample growth opportunities in the Data Science Platform market. Owing to a rapidly proliferating technology-backed economical structure, APAC is expected to emerge as the fastest-growing region in Data Science Platform software and services demand during the forecast period.

Given below is the breakup of the primary respondents:

  • By Company Type: Tier 1 - 34%, Tier 2 - 43%, and Tier 3 - 23%
  • By Designation: C-level - 50%, Directors - 30%, and Others - 20%
  • By Region: North America - 30%, Europe - 30%, APAC - 25%, MEA - 10%, Latin America- 5%.

Some prominent players profiled in the study include IBM(US), Google(US), Microsoft(US), SAS(US), AWS(US), MathWorks (US), Cloudera (US), Teradata (US), TIBCO (US), Alteryx (US), RapidMiner (US), Databricks (US), Snowflake (US), H2O.ai (US), Altair (US), Anaconda (US), SAP (US), Domino Data Lab (US), Dataiku (US), DataRobot (US), Apheris (Germany), Comet (US), Databand (US), dotData (US), Explorium (US), Noogata (US), Tecton (US), Spell (US), Arrikto (US), and Iterative (US).

Research Coverage

The market study covers Data Science Platform across different segments. It aims at estimating the market size and the growth potential of this market across different segments, such as, by Component (Platform & Services), Business Function (Marketing, Sales, Logistics, & Customer Support), Deployment Mode, Organization Size, Industry Vertical, and Region. The regional analysis of the Data Science Platform covers North America, Europe, APAC, MEA, and Latin America

The study also includes an in-depth competitive analysis of the key market players, along with their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.

Key benefits of buying the report

The report is expected to help the market leaders/new entrants in this market by providing them information on the closest approximations of the revenue numbers for the overall Data Science Platform and its segments. This report is also expected to help stakeholders understand the competitive landscape and gain insights to improve the position of their businesses and plan suitable go-to-market strategies. The report also aims at helping stakeholders understand the pulse of the market and provide them with information on key market drivers, restraints, challenges, and opportunities.

Frequently Asked Questions about the Global Data Science Platform Market

What is the estimated value of the Global Data Science Platform Market?

The Global Data Science Platform Market was estimated to be valued at $95.3 Billion in 2021.

What is the growth rate of the Global Data Science Platform Market?

The growth rate of the Global Data Science Platform Market is 27.6%, with an estimated value of $322.9 Billion by 2026.

What is the forecasted size of the Global Data Science Platform Market?

The Global Data Science Platform Market is estimated to be worth $322.9 Billion by 2026.

Who are the key companies in the Global Data Science Platform Market?

Key companies in the Global Data Science Platform Market include Ibm, Google, Microsoft, Mathworks, Sas, Cloudera, Teradata, Tibco, Aws and Alteryx.

Table of Contents

1 Introduction
1.1 Objectives of the Study
1.2 Market Definition
1.2.1 Inclusions and Exclusions
1.3 Market Scope
1.3.1 Market Segmentation
1.3.2 Regions Covered
1.4 Years Considered for the Study
1.5 Currency Considered
1.6 Stakeholders
2 Research Methodology
2.1 Research Data
2.1.1 Secondary Data
2.1.2 Primary Data
2.1.2.1 Breakup of Primaries
2.1.2.2 Key Industry Insights
2.2 Data Triangulation
2.3 Market Size Estimation
2.4 Market Forecast
2.5 Assumptions for the Study
2.6 Limitations of the Study
3 Executive Summary
4 Premium Insights
4.1 Attractive Opportunities in the Data Science Platform Market
4.2 Market: Top 3 Business Functions
4.3 Market: By Region
4.4 Market in North America, By Business Function and Industry Vertical
5 Market Overview and Industry Trends
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.1.1 Enterprises Focusing on Ease of use Methods to Drive Business
5.2.1.2 Growing Need to Extract In-Depth Insights From Voluminous Data to Gain Competitive Advantage
5.2.2 Restraints
5.2.2.1 Stringent Government Rules and Regulations
5.2.3 Opportunities
5.2.3.1 Higher Inclination of Enterprises Toward Data-Intensive Business Strategies
5.2.3.2 Rise in Adoption of Advanced Technologies
5.2.4 Challenges
5.2.4.1 Lack of Adequately Skilled Workforce
5.2.4.2 Data Privacy, Security, and Reliability Concerns
5.3 Industry Trends
5.3.1 Value Chain Analysis
5.3.2 Use Cases
5.3.2.1 Use Case: Scenario 1
5.3.2.2 Use Case: Scenario 2
5.3.2.3 Use Case: Scenario 3
5.4 Impact of Technologies on Data Science Platform
5.4.1 Machine Learning
5.4.2 Deep Learning
5.4.3 Natural Language Processing
5.5 Regulatory Implications
5.5.1 General Data Protection Regulation
5.5.2 The International Organization for Standardization 27001
5.5.3 Payment Card Industry Data Security Standard
5.5.4 Basel Committee on Banking Supervision 239 Compliance
5.5.5 California Consumer Privacy Act
5.5.6 Health Insurance Portability and Accountability Act of 1996
5.5.7 Health Information Technology for Economic and Clinical Health Act
5.5.8 Sarbanes-Oxley Act of 2002
5.5.9 Personal Data Protection Act
6 Data Science Platform Market, By Component
6.1 Introduction
6.2 Platform
6.2.1 Platform: Market Driver
6.3 Services
6.3.1 Managed Services
6.3.1.1 Managed Services: Market Drivers
6.3.2 Professional Services
6.3.2.1 Training and Consulting
6.3.2.1.1 Training and Consulting: Market Drivers
6.3.2.2 Integration and Deployment
6.3.2.2.1 Integration and Deployment: Market Driver
6.3.2.3 Support and Maintenance
6.3.2.3.1 Support and Maintenance: Market Drivers
7 Market, By Deployment Mode
7.1 Introduction
7.2 On-Premises
7.2.1 On-Premises: Market Drivers
7.3 Cloud
7.3.1 Cloud: Market Drivers
8 Data Science Platform Market, By Organization Size
8.1 Introduction
8.2 Large Enterprises
8.2.1 Large Enterprises: Market Drivers
8.3 Small and Medium-Sized Enterprises
8.3.1 Small and Medium-Sized Enterprises: Market Driver
9 Market, By Business Function
9.1 Introduction
9.2 Marketing
9.2.1 Marketing: Market Drivers
9.3 Sales
9.3.1 Sales: Market Drivers
9.4 Logistics
9.4.1 Logistics: Market Drivers
9.5 Finance and Accounting
9.5.1 Finance and Accounting: Market Drivers
9.6 Customer Support
9.6.1 Customer Support: Market Drivers
9.7 Others
9.7.1 Others: Market Drivers
10 Market, By Industry Vertical
10.1 Introduction
10.2 Banking, Financial Services, and Insurance
10.2.1 Banking, Financial Services, and Insurance: Market Drivers
10.3 Telecom and IT
10.3.1 Telecom and IT: Data Science Platform Market Driver
10.4 Retail and Ecommerce
10.4.1 Retail and Ecommerce: Market Drivers
10.5 Healthcare and Life Sciences
10.5.1 Healthcare and Life Sciences: Market Drivers
10.6 Manufacturing
10.6.1 Manufacturing: Market Drivers
10.7 Energy and Utilities
10.7.1 Energy and Utilities: Market Drivers
10.8 Media and Entertainment
10.8.1 Media and Entertainment: Market Drivers
10.9 Transportation and Logistics
10.9.1 Transportation and Logistics: Market Driver
10.10 Government and Defense
10.10.1 Government and Defense: Market Drivers
10.11 Others
11 Data Science Platform Market, By Region
11.1 Introduction
11.2 North America
11.2.1 United States
11.2.1.1 United States: Market Drivers
11.2.2 Canada
11.2.2.1 Canada: Market Driver
11.3 Europe
11.3.1 United Kingdom
11.3.1.1 United Kingdom: Market Driver
11.3.2 Germany
11.3.2.1 Germany: Market Driver
11.3.3 France
11.3.3.1 France: Market Driver
11.3.4 Rest of Europe
11.4 Asia Pacific
11.4.1 China
11.4.1.1 China: Market Driver
11.4.2 Japan
11.4.2.1 Japan: Market Driver
11.4.3 India
11.4.3.1 India: Data Science Platform Market Driver
11.4.4 Rest of Asia Pacific
11.5 Middle East and Africa
11.5.1 Middle East
11.5.1.1 Middle East: Market Driver
11.5.2 South Africa
11.5.2.1 South Africa: Market Driver
11.6 Latin America
11.6.1 Brazil
11.6.1.1 Brazil: Market Driver
11.6.2 Mexico
11.6.2.1 Mexico: Market Driver
11.6.3 Rest of Latin America
12 Competitive Landscape
12.1 Overview
12.2 Competitive Leadership Mapping
12.2.1 Visionary Leaders
12.2.2 Innovators
12.2.3 Dynamic Differentiators
12.2.4 Emerging Companies
13 Company Profiles
13.1 Introduction
13.2 Microsoft
13.3 IBM
13.4 Google
13.5 SAS Institute
13.6 Altair
13.7 Cloudera
13.8 Alteryx
13.9 Databricks
13.10 Wolfram
13.11 MathWorks
13.12 RapidMiner
13.13 Anaconda
13.14 Bridgei2i
13.15 Rexer Analytics
13.16 Domino Data Lab
13.17 Dataiku
13.18 Civis Analytics
13.19 H2O.Ai
13.20 RStudio
13.21 Rapid Insight
13.22 SAP
14 Appendix
14.1 Industry Experts
14.2 Discussion Guide
14.3 Knowledge Store: Subscription Portal
14.4 Available Customizations
14.5 Related Reports
14.6 Author Details
List of Tables:
Table 1 United States Dollar Exchange Rate, 2015–2018
Table 2 Factor Analysis
Table 3 Global Data Science Platform Market Size and Growth Rate, 2017–2024 (USD Million, Y-O-Y %)
Table 4 Market Size, By Component, 2017–2024 (USD Million)
Table 5 Platform: Market Size, By Region, 2017–2024 (USD Million)
Table 6 Services: Market Size, By Type, 2017–2024 (USD Million)
Table 7 Services: Market Size, By Region, 2017–2024 (USD Million)
Table 8 Managed Services Market Size, By Region, 2017–2024 (USD Million)
Table 9 Professional Services: Market Size, By Region, 2017–2024 (USD Million)
Table 10 Training and Consulting Market Size, By Region, 2017–2024 (USD Million)
Table 11 Integration and Deployment Market Size, By Region, 2017–2024 (USD Million)
Table 12 Support and Maintenance Market Size, By Region, 2017–2024 (USD Million)
Table 13 Data Science Platform Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 14 On-Premises: Market Size, By Region, 2017–2024 (USD Million)
Table 15 Cloud: Market Size, By Region, 2017–2024 (USD Million)
Table 16 Market Size, By Organization Size, 2017–2024 (USD Million)
Table 17 Large Enterprises: Market Size, By Region, 2017–2024 (USD Million)
Table 18 Small and Medium-Sized Enterprises:Market Size, By Region, 2017–2024 (USD Million)
Table 19 Market Size, By Business Function, 2017–2024 (USD Million)
Table 20 Marketing: Market Size, By Region, 2017–2024 (USD Million)
Table 21 Data Science Platform Market Size, By Region, 2017–2024 (USD Million)
Table 22 Logistics: Market Size, By Region, 2017–2024 (USD Million)
Table 23 Finance and Accounting: Market Size, By Region, 2017–2024 (USD Million)
Table 24 Customer Support: Market Size, By Region, 2017–2024 (USD Million)
Table 25 Others: Market Size, By Region, 2017–2024 (USD Million)
Table 26 Market Size, By Industry Vertical, 2017–2024 (USD Million)
Table 27 Banking, Financial Services, and Insurance: Data Science Platform Market Size, By Region, 2017–2024 (USD Million)
Table 28 Telecom and IT: Market Size, By Region, 2017–2024 (USD Million)
Table 29 Retail and Ecommerce: Market Size, By Region, 2017–2024 (USD Million)
Table 30 Healthcare and Life Sciences: Market Size, By Region, 2017–2024 (USD Million)
Table 31 Manufacturing: Market Size, By Region, 2017–2024 (USD Million)
Table 32 Energy and Utilities: Market Size, By Region, 2017–2024 (USD Million)
Table 33 Media and Entertainment: Market Size, By Region, 2017–2024 (USD Million)
Table 34 Transportation and Logistics: Market Size, By Region, 2017–2024 (USD Million)
Table 35 Government and Defense: Market Size, By Region, 2017–2024 (USD Million)
Table 36 Others: Market Size, By Region, 2017–2024 (USD Million)
Table 37 Market Size, By Region, 2017–2024 (USD Million)
Table 38 North America: Data Science Platform Market Size, By Component, 2017–2024 (USD Million)
Table 39 North America: Market Size, By Service, 2017–2024 (USD Million)
Table 40 North America: Market Size, By Professional Service, 2017–2024 (USD Million)
Table 41 North America: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 42 North America: Market Size, By Organization Size, 2017–2024 (USD Million)
Table 43 North America: Market Size, By Business Function, 2017–2024 (USD Million)
Table 44 North America: Market Size, By Industry Vertical, 2017–2024 (USD Million)
Table 45 North America: Market Size, By Country, 2017–2024 (USD Million)
Table 46 United States: Data Science Platform Market Size, By Component, 2017–2024 (USD Million)
Table 47 United States: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 48 Canada: Market Size, By Component, 2017–2024 (USD Million)
Table 49 Canada: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 50 Europe: Market Size, By Component, 2017–2024 (USD Million)
Table 51 Europe: Market Size, By Service, 2017–2024 (USD Million)
Table 52 Europe: Market Size, By Professional Service, 2017–2024 (USD Million)
Table 53 Europe: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 54 Europe: Data Science Platform Market Size, By Organization Size, 2017–2024 (USD Million)
Table 55 Europe: Market Size, By Business Function, 2017–2024 (USD Million)
Table 56 Europe: Market Size, By Industry Vertical, 2017–2024 (USD Million)
Table 57 Europe: Market Size, By Country, 2017–2024 (USD Million)
Table 58 United Kingdom: Market Size, By Component, 2017–2024 (USD Million)
Table 59 United Kingdom: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 60 Germany: Market Size, By Component, 2017–2024 (USD Million)
Table 61 Germany: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 62 France: Market Size, By Component, 2017–2024 (USD Million)
Table 63 France: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 64 Asia Pacific: Data Science Platform Market Size, By Component, 2017–2024 (USD Million)
Table 65 Asia Pacific: Market Size, By Service, 2017–2024 (USD Million)
Table 66 Asia Pacific: Market Size, By Professional Service, 2017–2024 (USD Million)
Table 67 Asia Pacific: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 68 Asia Pacific: Market Size, By Organization Size, 2017–2024 (USD Million)
Table 69 Asia Pacific: Market Size, By Business Function, 2017–2024 (USD Million)
Table 70 Asia Pacific: Market Size, By Industry Vertical, 2017–2024 (USD Million)
Table 71 Asia Pacific: Market Size, By Country, 2017–2024 (USD Million)
Table 72 China: Data Science Platform Market Size, By Component, 2017–2024 (USD Million)
Table 73 China: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 74 Japan: Market Size, By Component, 2017–2024 (USD Million)
Table 75 Japan: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 76 India: Market Size, By Component, 2017–2024 (USD Million)
Table 77 India: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 78 Middle East and Africa: Market Size, By Component, 2017–2024 (USD Million)
Table 79 Middle East and Africa: Market Size, By Service, 2017–2024 (USD Million)
Table 80 Middle East and Africa: Market Size, By Professional Service, 2017–2024 (USD Million)
Table 81 Middle East and Africa: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 82 Middle East and Africa: Data Science Platform Market Size, By Organization Size, 2017–2024 (USD Million)
Table 83 Middle East and Africa: Market Size, By Business Function, 2017–2024 (USD Million)
Table 84 Middle East and Africa: Market Size, By Industry Vertical, 2017–2024 (USD Million)
Table 85 Middle East and Africa: Market Size, By Country, 2017–2024 (USD Million)
Table 86 Middle East: Market Size, By Component, 2017–2024 (USD Million)
Table 87 Middle East: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 88 South Africa: Market Size, By Component, 2017–2024 (USD Million)
Table 89 South Africa: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 90 Latin America: Data Science Platform Market Size, By Component, 2017–2024 (USD Million)
Table 91 Latin America: Market Size, By Service, 2017–2024 (USD Million)
Table 92 Latin America: Market Size, By Professional Service, 2017–2024 (USD Million)
Table 93 Latin America: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 94 Latin America: Market Size, By Organization Size, 2017–2024 (USD Million)
Table 95 Latin America: Market Size, By Business Function, 2017–2024 (USD Million)
Table 96 Latin America: Market Size, By Industry Vertical, 2017–2024 (USD Million)
Table 97 Latin America: Market Size, By Country, 2017–2024 (USD Million)
Table 98 Brazil: Data Science Platform Market Size, By Component, 2017–2024 (USD Million)
Table 99 Brazil: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 100 Mexico: Market Size, By Component, 2017–2024 (USD Million)
Table 101 Mexico: Market Size, By Deployment Mode, 2017–2024 (USD Million)
Table 102 Evaluation Criteria
List of Figures:
Figure 1 Data Science Platform Market: Research Design
Figure 2 Market Size Estimation Methodology: Approach 1 (Supply Side): Revenue of Products/Solutions/Services of Data Science  Platform Market
Figure 3 Market Size Estimation Methodology: Approach 1 Bottom-Up (Supply Side): Collective Revenue of All Products/Solutions/Services of Market
Figure 4 Market Size Estimation Methodology: Approach 2 Bottom-Up (Demand Side): Products/Solutions/Services Sold and Their Average Selling Price
Figure 5 Market, By Component
Figure 6 Market, By Service
Figure 7 Market, By Professional Service
Figure 8 Market, By Deployment Mode
Figure 9 Market, By Organization Size
Figure 10 Market, By Business Function
Figure 11 Market, By Industry Vertical
Figure 12 Data Science Platform Market, By Region
Figure 13 Rise in Adoption of Advanced Technologies, Such as Ai and Analytics, and Higher Inclination of Enterprises Toward Data-Intensive Business Strategies Driving the Overall Growth of the Market
Figure 14 Marketing Segment to Hold the Largest Market Size During the Forecast Period
Figure 15 North America to Hold the Highest Market Share in 2019
Figure 16 Marketing Segment and Banking, Financial Services, and Insurance Industry Vertical Accounted for the Highest Shares in the Market in 2019
Figure 17 Drivers, Restraints, Opportunities, and Challenges: Market
Figure 18 Value Chain Analysis: Data Science Platform Market
Figure 19 Services Segment to Register a Higher CAGR During the Forecast Period
Figure 20 Managed Services Segment to Grow at a Higher CAGR During the Forecast Period
Figure 21 Support and Maintenance Segment to Grow at the Highest CAGR During the Forecast Period
Figure 22 Cloud Segment to Register a Higher CAGR During the Forecast Period
Figure 23 Small and Medium-Sized Enterprises Segment to Register a Higher CAGR During the Forecast Period
Figure 24 Logistics Segment to Register the Highest CAGR During the Forecast Period
Figure 25 Banking, Financial Services, and Insurance Industry Vertical to Hold the Largest Market Size During the Forecast Period
Figure 26 North America to Account for the Largest Market Size During the Forecast Period
Figure 27 India to Register the Highest CAGR During the Forecast Period
Figure 28 Asia Pacific to Grow at the Highest CAGR During the Forecast Period
Figure 29 North America: Market Snapshot
Figure 30 Logistics Segment to Register the Highest CAGR During the Forecast Period
Figure 31 Logistics Segment to Grow at the Highest CAGR During the Forecast Period
Figure 32 Asia Pacific: Market Snapshot
Figure 33 Logistics Segment to Grow at the Highest CAGR During the Forecast Period
Figure 34 Logistics to Grow at the Highest CAGR During the Forecast Period
Figure 35 Logistics Segment to Grow at the Highest CAGR During the Forecast Period
Figure 36 Data Science Platform Market (Global), Competitive Leadership Mapping, 2019
Figure 37 Microsoft: Company Snapshot
Figure 38 SWOT Analysis: Microsoft
Figure 39 IBM: Company Snapshot
Figure 40 SWOT Analysis: IBM
Figure 41 Google: Company Snapshot
Figure 42 SWOT Analysis: Google
Figure 43 SAS Institute: Company Snapshot
Figure 44 SWOT Analysis: SAS Institute
Figure 45 Altair: Company Snapshot
Figure 46 SWOT Analysis: Altair
Figure 47 Cloudera: Company Snapshot
Figure 48 Alteryx: Company Snapshot

Executive Summary

Companies Mentioned

  • Ibm
  • Google
  • Microsoft
  • Mathworks
  • Sas
  • Cloudera
  • Teradata
  • Tibco
  • Aws
  • Alteryx
  • Rapidminer
  • Databricks
  • Snowflake
  • H2O.Ai
  • Anaconda
  • Altair
  • Sap
  • Domino Data Lab
  • Dataiku
  • Datarobot
  • Apheris
  • Comet
  • Databand
  • Dotdata
  • Explorium
  • Noogata
  • Tecton
  • Spell
  • Arrikto
  • Iterative

Methodology

Loading
LOADING...