Data Science Platform Market by Business Function (Marketing, Sales, Logistics, Risk, Customer Support, Human Resources, & Operations), Deployment Model, Vertical, and Region - Global Forecast to 2021

The data science platform market size is estimated to grow from USD 19.58 Billion in 2016 to USD 101.37 Billion by 2021, at a Compound Annual Growth Rate (CAGR) of 38.9% during the forecast period. The base year considered for this report is 2015 and the forecast period is 2016–2021.

Objectives of the Study:

The main objective of this report is to define, describe, and forecast the global data science platform market, on the basis of business functions, deployment models, verticals, and regions. The report provides detailed information regarding the major factors influencing the growth of the market (drivers, restraints, opportunities, and industry-specific challenges). It aims to strategically analyze micro markets with respect to individual growth trends, future prospects, and contribution to the total market. The report attempts to forecast the market size with respect to five main regions, namely, North America, Europe, Asia-Pacific (APAC), Middle East & Africa (MEA), and Latin America. It strategically profiles key players and comprehensively analyzes their core competencies. This report also tracks and analyzes competitive developments, such as joint ventures, acquisitions, new product developments, and Research & Development (R&D) activities in the market.

The research methodology used to estimate and forecast the data science platform market begins with capturing data on the key vendor’s revenues through a secondary research. The sources referred for secondary research include Hoovers, Bloomberg Businessweek, Factiva, and OneSource. The vendor offerings are also taken into consideration to determine the market segmentation. The bottom-up procedure was employed to arrive at the overall market size of the global market from the revenue of the key players in the market. After arriving at the overall market size, the total market was split into several segments and subsegments, which were then verified through primary research by conducting extensive interviews with key people, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), directors, and executives. The data triangulation and market breakdown procedures were employed to complete the overall market engineering process and to arrive at the exact statistics for all segments and subsegments. The breakdown of primary profiles is depicted in the below figure:

To know about the assumptions considered for the study, download the pdf brochure

The data science platform market ecosystem comprises solutions and service providers, such as Microsoft Corporation (U.S.), IBM Corporation (U.S.), Google, Inc. (U.S.), Wolfram (U.S.), DataRobot Inc. (U.S.), Sense Inc. (U.S.), RapidMiner Inc. (U.S.), Domino Data Lab (U.S.), Dataiku (France), Alteryx, Inc. (U.S.), and Continuum Analytics, Inc. (U.S.).

Key Target Audience:

• Independent Software Vendors
• Business Analytics Software Providers
• IT Service Providers
• Cloud Service Providers
• System Integrators
• Application Design and Software Developers

“Study answers several questions for the stakeholders, primarily which market segments will focus in the next two to five years for prioritizing the efforts and investments”.

Scope of the Data Science Platform Market Research Report:

The research report categorizes the data science platform market to forecast the revenues and analyzes the trends in each of the following subsegments:

By Business Function:

• Marketing
• Sales
• Logistics
• Risk
• Customer Support
• Human Resources
• Operations

By Deployment Model:

• On-Premises
• On-Demand

By Vertical:

• Banking, Financial Services, and Insurance (BFSI)
• Healthcare and Life Sciences
• Information Technology and Telecom
•  Retail and Consumer Goods
• Media and Entertainment
• Manufacturing
• Transportation and Logistics
• Energy and Utilities
• Government and Defense
• Others

By Region:

• North America
• Europe
• MEA
• APAC
• Latin America

Available Customizations:

With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:

Product Analysis:

Product matrix gives a detailed comparison of product portfolio of each company.

Geographic Analysis:

• Further breakdown of the North America data science platform market
• Further breakdown of the Europe market
• Further breakdown of the APAC market
• Further breakdown of the MEA market
• Further breakdown of the Latin America market

Company Information:

• Detailed analysis and profiling of additional market players

Table of Contents

1 Introduction (Page No. - 13)
    1.1 Objectives of the Study
    1.2 Market Definition
    1.3 Market Scope
           1.3.1 Markets Covered
           1.3.2 Years Considered in the Report
    1.4 Currency
    1.5 Limitations
    1.6 Stakeholders

2 Research Methodology (Page No. - 16)
    2.1 Research Data
           2.1.1 Secondary Data
                    2.1.1.1 Key Data From Secondary Sources
           2.1.2 Primary Data
                    2.1.2.1 Key Data From Primary Sources
                    2.1.2.2 Key Industry Insights
                    2.1.2.3 Breakdown of Primaries
    2.2 Market Size Estimation
    2.3 Market Breakdown and Data Triangulation
    2.4 Research Assumptions

3 Executive Summary (Page No. - 24)

4 Premium Insights (Page No. - 28)
    4.1 Attractive Market Opportunities in the Data Science Platform Market
    4.2 Market: By Top Three Business Functions and Regions
    4.3 Lifecycle Analysis, By Region
    4.4 Market Investment Scenario
    4.5 Market: Top Three Verticals

5 Market Overview (Page No. - 31)
    5.1 Introduction
    5.2 Market Segmentation
           5.2.1 By Business Function
           5.2.2 By Deployment Model
           5.2.3 By Vertical
           5.2.4 By Region
    5.3 Market Evolution
    5.4 Market Dynamics
           5.4.1 Drivers
                    5.4.1.1 Enterprises are Focusing on Ease of Use Methods to Drive Their Business
                    5.4.1.2 Advancement in Big Data Technologies
           5.4.2 Restraints
                    5.4.2.1 Lack of Reliability on Data Science Among the Enterprises
                    5.4.2.2 Government Rules and Regulations
                    5.4.2.3 Data Governance
           5.4.3 Opportunities
                    5.4.3.1 Higher Inclination of Enterprises Toward Data Intensive Business Strategies
                    5.4.3.2 High Roi Through End-To-End Data Science Platform Implementation
           5.4.4 Challenges
                    5.4.4.1 High Investment Cost
                    5.4.4.2 Data Privacy, Security, and Reliability
                    5.4.4.3 Requirement to Constantly Update the Data Science Platform to Cope With Advanced Data Sources, Tools, and Technologies

6 Industry Trends (Page No. - 39)
    6.1 Introduction
    6.2 Value Chain Analysis
    6.3 Data Science Platform Use Cases
           6.3.1 Introduction
                    6.3.1.1 Customer Relationship Analytics
                    6.3.1.2 Human Resource Analytics
                    6.3.1.3 Clinical Trial Medication Compliance
                    6.3.1.4 Digital Agriculture
                    6.3.1.5 Churn Analytics
    6.4 Data Science Platform Ecosystem

7 Data Science Platform Market, By Business Function (Page No. - 44)
    7.1 Introduction
    7.2 Marketing
    7.3 Sales
    7.4 Logistics
    7.5 Risk
    7.6 Customer Support
    7.7 Human Resources
    7.8 Operations

8 Data Science Platform Market Analysis, By Deployment Model (Page No. - 53)
    8.1 Introduction
    8.2 On-Premises
    8.3 On-Demand

9 Data Science Platform Market Analysis, By Vertical (Page No. - 57)
    9.1 Introduction
    9.2 Banking, Financial Services, and Insurance
    9.3 Healthcare and Life Sciences
    9.4 IT and Telecom
    9.5 Retail and Consumer Goods
    9.6 Media and Entertainment
    9.7 Manufacturing
    9.8 Transportation and Logistics
    9.9 Energy and Utilities
    9.10 Government and Defense
    9.11 Others

10 Geographic Analysis (Page No. - 70)
     10.1 Introduction
     10.2 North America
     10.3 Europe
     10.4 APAC
     10.5 Latin America
     10.6 Middle East and Africa

11 Competitive Landscape (Page No. - 85)
     11.1 Overview
     11.2 Competitive Situations and Trends
             11.2.1 Partnerships, Collaborations, and Agreements
             11.2.2 New Product Launches
             11.2.3 Expansions
             11.2.4 Acquisition
     11.3 Data Science Platform Market: Vendor Comparison
     11.4 Vendor Inclusion Criteria
     11.5 Vendors Evaluated

12 Company Profiles (Page No. - 96)
     12.1 Introduction
     12.2 Microsoft
(Business Overview, Products Offered, Recent Developments, MnM View, SWOT Analysis, and Key Strategies)
     12.3 IBM
     12.4 Google
     12.5 Wolfram
     12.6 Datarobot
     12.7 Cloudera
     12.8 Rapidminer
     12.9 Domino Data Lab
     12.10 Dataiku
     12.11 Alteryx
     12.12 Continuum Analytics
*Details on Business Overview, Products Offered, Recent Developments, MnM View, SWOT Analysis, and Key Strategies Might Not Be Captured in Case of Unlisted Companies.
     12.13 Key Innovators
             12.13.1 Bridgei2i Analytics
             12.13.2 Datarpm
             12.13.3 Rexer Analytics
             12.13.4 Feature Labs
             12.13.5 Civis Analytics

13 Appendix (Page No. - 128)
     13.1 Key Insights
     13.2 Discussion Guide
     13.3 Knowledge Store: Marketsandmarkets’ Subscription Portal
     13.4 Introducing RT: Real-Time Market Intelligence
     13.5 Available Customization
     13.6 Related Reports
     13.7 Author Details

List of Tables (44 Tables)

Table 1 Data Science Platform Market Size and Growth, 2014–2021 (USD Billion, Y-O-Y %)
Table 2 Market Size, By Business Function, 2014–2021 (USD Billion)
Table 3 Marketing: Market Size, By Region, 2014–2021 (USD Million)
Table 4 Sales: Market Size, By Region, 2014–2021 (USD Million)
Table 5 Logistics: Market Size, By Region, 2014–2021 (USD Million)
Table 6 Risk: Market Size, By Region, 2014–2021 (USD Million)
Table 7 Customer Support: Market Size, By Region, 2014–2021 (USD Million)
Table 8 Human Resources: Market Size, By Region, 2014–2021 (USD Million)
Table 9 Operations: Market Size, By Region, 2014–2021 (USD Million)
Table 10 Market Size, By Deployment Model, 2014–2021 (USD Billion)
Table 11 On-Premises: Market Size, By Region, 2014–2021 (USD Million)
Table 12 On-Demand: Market Size, By Region, 2014–2021 (USD Million)
Table 13 Data Science Platform Market Size, By Vertical, 2014–2021 (USD Billion)
Table 14 BFSI: Market Size, By Region, 2014–2021 (USD Million)
Table 15 Healthcare and Life Sciences: Market Size, By Region, 2014–2021 (USD Million)
Table 16 IT and Telecom: Market Size, By Region, 2014–2021 (USD Million)
Table 17 Retail and Consumer Goods: Market Size, By Region, 2014–2021 (USD Million)
Table 18 Media and Entertainment: Market Size, By Region, 2014–2021 (USD Million)
Table 19 Manufacturing: Market Size, By Region, 2014–2021 (USD Million)
Table 20 Transportation and Logistics: Market Size, By Region, 2014–2021 (USD Million)
Table 21 Energy and Utilities: Market Size, By Region, 2014–2021 (USD Million)
Table 22 Government and Defense: Market Size, By Region, 2014–2021 (USD Million)
Table 23 Others: Market Size, By Region, 2014–2021 (USD Million)
Table 24 Market Size, By Region, 2014–2021 (USD Billion)
Table 25 North America: Data Science Platform Market Size, By Vertical, 2014–2021 (USD Billion)
Table 26 North America: Market Size, By Business Function, 2014–2021 (USD Billion)
Table 27 North America: Market Size, By Deployment Model, 2014–2021 (USD Million)
Table 28 Europe: Market Size, By Vertical, 2014–2021 (USD Billion)
Table 29 Europe: Market Size, By Business Function, 2014–2021 (USD Million)
Table 30 Europe: Market Size, By Deployment Model, 2014–2021 (USD Million)
Table 31 APAC: Data Science Platform Market Size, By Vertical, 2014–2021 (USD Billion)
Table 32 APAC: Market Size, By Business Function, 2014–2021 (USD Billion)
Table 33 APAC: Market Size, By Deployment Model, 2014–2021 (USD Million)
Table 34 Latin America: Market Size, By Vertical, 2014–2021 (USD Million)
Table 35 Latin America: Market Size, By Business Function, 2014–2021 (USD Billion)
Table 36 Latin America: Market Size, By Deployment Model, 2014–2021 (USD Billion)
Table 37 MEA: Data Science Platform Market Size, By Vertical, 2014–2021 (USD Million)
Table 38 MEA: Market Size, By Business Function, 2014–2021 (USD Million)
Table 39 MEA: Market Size, By Deployment Model, 2014–2021 (USD Million)
Table 40 Partnerships, Agreements, and Collaborations, 2014–2017
Table 41 New Product Launches, 2014-2016
Table 42 Expansions, 2014-2016
Table 43 Acquisitions, 2015–2016
Table 44 Evaluation Criteria

List of Figures (43 Figures)

Figure 1 Data Science Platform Market: Market Segmentation
Figure 2 Market: Research Design
Figure 3 Breakdown of Primary Interviews: By Company, Designation, and Region
Figure 4 Market Size Estimation Methodology: Bottom-Up Approach
Figure 5 Market Size Estimation Methodology: Top-Down Approach
Figure 6 Data Triangulation
Figure 7 Data Science Platform Market: Assumptions
Figure 8 Top Three Largest Revenue Segments of the Market, 2016
Figure 9 North America is Expected to Hold the Largest Market Share in the Market
Figure 10 Advancement in the Big Data Technology is Expected to Drive Growth of the Market During the Forecast Period
Figure 11 Logistics Business Function is Expected to Hold the Largest Market Share in the Market in 2016
Figure 12 APAC is Expected to Have the Highest Growth Opportunity in the Market During the Forecast Period
Figure 13 Market Investment Scenario: APAC is the Best Market to Invest in During the Forecast Period
Figure 14 BFSI, is Estimated to Have the Largest Market Size During the Forecast Period
Figure 15 Data Science Platform Market Segmentation: By Business Function
Figure 16 Market Segmentation: By Deployment Model
Figure 17 Market Segmentation: By Vertical
Figure 18 Market Segmentation: By Region
Figure 19 Evolution of the Market
Figure 20 Market: Drivers, Restraints, Opportunities, and Challenges
Figure 21 Market: Value Chain Analysis
Figure 22 Logistics Business Function is Expected to Have the Largest Market Size During the Forecast Period
Figure 23 On-Premises Deployment Model is Expected to Have the Larger Market Size During Forecast Period
Figure 24 Retail and Consumer Goods Vertical is Expected to Have the Largest Market Size By 2021
Figure 25 North America is Expected to Have the Largest Market Size in the Data Science Platform Market During the Forecast Period
Figure 26 North America Market Snapshot
Figure 27 APAC Market Snapshot
Figure 28 Companies Adopted Partnerships, Collaborations, and Agreements as Their Key Growth Strategy From 2012 to 2016
Figure 29 Market Evaluation Framework
Figure 30 Battle for Market Share: Partnerships, Collaborations, and Agreements, and New Product Launches Were the Key Strategies in the Data Science Platform Market
Figure 31 Evaluation Overview Table: Product Offering
Figure 32 Evaluation Overview Table: Business Strategy
Figure 33 Geographic Revenue Mix of the Top Three Market Players
Figure 34 Microsoft: Company Snapshot
Figure 35 Microsoft: SWOT Analysis
Figure 36 IBM: Company Snapshot
Figure 37 IBM: SWOT Analysis
Figure 38 Google: Company Snapshot
Figure 39 Google: SWOT Analysis
Figure 40 Wolfram: SWOT Analysis
Figure 41 Datarobot: SWOT Analysis
Figure 42 Cloudera: SWOT Analysis
Figure 43 Rapidminer: SWOT Analysis

The data science platform market is estimated to grow from USD 19.58 Billion in 2016 to USD 101.37 Billion by 2021, at a high Compound Annual Growth Rate (CAGR) of 38.9% during the forecast period. Enterprises focusing on methods enabling simpler use of data to drive their business and advancement in big data technologies are the key drivers that propel the growth of the  market.

The report provides detailed insights into the global market, which is segmented by business function, deployment model, vertical, and region. In business functions, the logistics segment holds the largest market share and is gaining significant importance among corporates & enterprises. In the logistics industry, customer satisfaction, global expansion, strong delivery & transport network, and presence of wide global/local presence are the most essential factors. Data scientists apply advanced mathematics and statistics to address numerous business queries that delivers insights to management, thereby maximizing the return on assets and high Returns on Investments (RoI).

The on-premises deployment model has a higher adoption, compared to the on-demand deployment model. The on-premises deployment model provides confidentiality and privacy parameters to the organizational data; hence, most of the organizations are adopting the on-premises deployment model. The Banking, Financial Services, and Insurance (BFSI) segment has shown the largest market share in vertical segment, where data science platform helps financial institutions to cut down on the risks that are likely to arise from the poor quality of data. Moreover, the growing data to fetch customer insights from the channels, such as Point of Sale (PoS) and Automated Teller Machine (ATM) has additionally enhanced the adoption of the data science platform market.  However, the manufacturing industry is poised to grow at the highest rate during the forecast period, where data science platform  will facilitate  data scientists to stream real-time analytics, ingesting from sensors and devices situated at the shop floor of the factory to make pertinent business decisions.

The North American market is expected to hold the largest market share, owing to capital intensive industries present across the region. Enterprises will looking to embrace data science platform as the revered platform will help them have a competitive edge in the marketplace. Further, the presence of mammoth players, such as IBM Corporation, Microsoft Corporation, and Google Inc. propel the demand of data science platform in this region.  The APAC market is anticipated to have the highest growth rate, owing to exponential increase in Foreign Direct Investments (FDIs), flexible government policies advocating the growth of digitalization, industrialization, and several smart city initiatives by various governments intensify the adoption of the data science platform market by leaps and bounds.

Lack of reliability on data science among enterprises, government rules & regulations, and data governance are the restraining factors for the data science platform market. High investment costs, data privacy &security, and reliability are some of the stumbling blocks in the adoption of data science platform solutions.

Most of the vendors have adopted agreements, collaborations & partnerships, new product launches, product upgradations, and expansions as the key strategy to enhance their client base & customer experience. For instance, in September 2016, Microsoft and Adobe entered into a strategic partnership to help enterprise companies embrace digital transformation and deliver compelling, personalized experiences through every phase of their customer relationship. This partnership will enable businesses to strengthen their brands through solutions with Microsoft Azure, Adobe Marketing Cloud, and Microsoft Dynamics 365. The strategy of new product launches has also been adopted by top players to innovate in this marketspace. For example, in October 2016, IBM launched Watson Data Platform that delivers data ingestion engine and cognitive powered decision-making tools that allows data scientists to leverage Artificial Intelligence (AI) for business use.

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