The global big data analytics in tourism market is expected to grow from USD 1.5 billion in 2016 to USD 3.2 billion by 2030, at a CAGR of 12.6% during the forecast period. The market is driven by the increasing demand for personalized services and customized travel packages, which are supported by big data analytics tools and solutions that help organizations understand their customers better and provide them with more personalized services. The large enterprises segment accounted for the largest share of the global market in 2016, followed by SMEs segment; however, this trend is expected to change over time as SMEs are increasingly adopting big data analytics solutions for their business operations. North America was the leading region in terms of revenue contribution in 2016; however, Asia Pacific is expected to be fastest-growing region during the forecast period due to its high adoption rate of new technologies such as cloud computing and IoT devices that support big data analytics applications across various industries including tourism industry.
- Big Data Analytics in Tourism market growth is driven by the need to provide personalized services to customers.
- Big Data Analytics in Tourism market growth is driven by the need for better customer service and increased revenue generation.
- Big Data Analytics in Tourism market growth is driven by the need for better customer service and increased revenue generation, which can be achieved through data analytics tools that help identify trends and patterns in customer behavior, such as what they buy, how often they buy it, when they buy it, where they buy it from etc, which helps companies understand their customers better and provide them with more personalized services or products that suit their needs best.
- The increasing number of tourists globally has led many countries around the world including India - one of the fastest growing economies -to invest heavily into tourism infrastructure development projects like hotels & resorts.
Industry Growth Insights published a new data on “Big Data Analytics in Tourism Market”. The research report is titled “Big Data Analytics in Tourism Market research by Types (Structured, Semi-Structured, Unstructured), By Applications (Large Enterprises, SMEs), By Players/Companies Hewlett Packard Enterprise, IBM, Microsoft, Oracle, Hitachi, SAP, Google, Amazon, Accenture, TIBCO, Tableau”.
Scope Of The Report
Report Attributes
Report Details
Report Title
Big Data Analytics in Tourism Market Research Report
By Type
Structured, Semi-Structured, Unstructured
By Application
Large Enterprises, SMEs
By Companies
Hewlett Packard Enterprise, IBM, Microsoft, Oracle, Hitachi, SAP, Google, Amazon, Accenture, TIBCO, Tableau
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
234
Number of Tables & Figures
164
Customization Available
Yes, the report can be customized as per your need.
Global Big Data Analytics in Tourism Market Report Segments:
The global Big Data Analytics in Tourism market is segmented on the basis of:
Types
Structured, Semi-Structured, Unstructured
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Large Enterprises, SMEs
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- Hewlett Packard Enterprise
- IBM
- Microsoft
- Oracle
- Hitachi
- SAP
- Google
- Amazon
- Accenture
- TIBCO
- Tableau
Highlights of The Big Data Analytics in Tourism Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- Structured
- Semi-Structured
- Unstructured
- By Application:
- Large Enterprises
- SMEs
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Big Data Analytics in Tourism Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
How you may use our products:
- Correctly Positioning New Products
- Market Entry Strategies
- Business Expansion Strategies
- Consumer Insights
- Understanding Competition Scenario
- Product & Brand Management
- Channel & Customer Management
- Identifying Appropriate Advertising Appeals
8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Big data analytics in tourism is the process of using large amounts of data to improve decision making and business operations. This can include things like understanding customer behavior, predicting trends, and improving marketing efforts.
Some of the major players in the big data analytics in tourism market are Hewlett Packard Enterprise, IBM, Microsoft, Oracle, Hitachi, SAP, Google, Amazon, Accenture, TIBCO, Tableau.
The big data analytics in tourism market is expected to register a CAGR of 12.6%.
1. Executive Summary
2. Assumptions and Acronyms Used
3. Research Methodology
4. Big Data Analytics in Tourism Market Overview
4.1. Introduction
4.1.1. Market Taxonomy
4.1.2. Market Definition
4.2. Macro-Economic Factors
4.2.1. Industry Outlook
4.3. Big Data Analytics in Tourism Market Dynamics
4.3.1. Market Drivers
4.3.2. Market Restraints
4.3.3. Opportunity
4.3.4. Market Trends
4.4. Big Data Analytics in Tourism Market - Supply Chain
4.5. Global Big Data Analytics in Tourism Market Forecast
4.5.1. Big Data Analytics in Tourism Market Size (US$ Mn) and Y-o-Y Growth
4.5.2. Big Data Analytics in Tourism Market Size (000 Units) and Y-o-Y Growth
4.5.3. Big Data Analytics in Tourism Market Absolute $ Opportunity
5. Global Big Data Analytics in Tourism Market Analysis and Forecast by Type
5.1. Market Trends
5.2. Introduction
5.2.1. Basis Point Share (BPS) Analysis by Type
5.2.2. Y-o-Y Growth Projections by Type
5.3. Big Data Analytics in Tourism Market Size and Volume Forecast by Type
5.3.1. Structured
5.3.2. Semi-Structured
5.3.3. Unstructured
5.4. Absolute $ Opportunity Assessment by Type
5.5. Market Attractiveness/Growth Potential Analysis by Type
6. Global Big Data Analytics in Tourism Market Analysis and Forecast by Application
6.1. Market Trends
6.2. Introduction
6.2.1. Basis Point Share (BPS) Analysis by Application
6.2.2. Y-o-Y Growth Projections by Application
6.3. Big Data Analytics in Tourism Market Size and Volume Forecast by Application
6.3.1. Large Enterprises
6.3.2. SMEs
6.4. Absolute $ Opportunity Assessment by Application
6.5. Market Attractiveness/Growth Potential Analysis by Application
7. Global Big Data Analytics in Tourism Market Analysis and Forecast by Sales Channel
7.1. Market Trends
7.2. Introduction
7.2.1. Basis Point Share (BPS) Analysis by Sales Channel
7.2.2. Y-o-Y Growth Projections by Sales Channel
7.3. Big Data Analytics in Tourism Market Size and Volume Forecast by Sales Channel
7.3.1. Manufacturer/Distributor/Service Provider
7.3.2. Aftermarket
7.4. Absolute $ Opportunity Assessment by Sales Channel
7.5. Market Attractiveness/Growth Potential Analysis by Sales Channel
8. Global Big Data Analytics in Tourism Market Analysis and Forecast by Region
8.1. Market Trends
8.2. Introduction
8.2.1. Basis Point Share (BPS) Analysis by Region
8.2.2. Y-o-Y Growth Projections by Region
8.3. Big Data Analytics in Tourism Market Size and Volume Forecast by Region
8.3.1. North America
8.3.2. Latin America
8.3.3. Europe
8.3.4. Asia Pacific
8.3.5. Middle East and Africa (MEA)
8.4. Absolute $ Opportunity Assessment by Region
8.5. Market Attractiveness/Growth Potential Analysis by Region
8.6. Global Big Data Analytics in Tourism Demand Share Forecast, 2019-2026
9. North America Big Data Analytics in Tourism Market Analysis and Forecast
9.1. Introduction
9.1.1. Basis Point Share (BPS) Analysis by Country
9.1.2. Y-o-Y Growth Projections by Country
9.2. North America Big Data Analytics in Tourism Market Size and Volume Forecast by Country
9.2.1. U.S.
9.2.2. Canada
9.3. Absolute $ Opportunity Assessment by Country
9.4. North America Big Data Analytics in Tourism Market Size and Volume Forecast by Application
9.4.1. Large Enterprises
9.4.2. SMEs
9.5. Basis Point Share (BPS) Analysis by Application
9.6. Y-o-Y Growth Projections by Application
9.7. North America Big Data Analytics in Tourism Market Size and Volume Forecast by Type
9.7.1. Structured
9.7.2. Semi-Structured
9.7.3. Unstructured
9.8. Basis Point Share (BPS) Analysis by Type
9.9. Y-o-Y Growth Projections by Type
9.10. Market Attractiveness/Growth Potential Analysis
9.10.1. By Country
9.10.2. By Product Type
9.10.3. By Application
9.10.4. By Sales Channel
9.11. North America Big Data Analytics in Tourism Demand Share Forecast, 2019-2026
10. Latin America Big Data Analytics in Tourism Market Analysis and Forecast
10.1. Introduction
10.1.1. Basis Point Share (BPS) Analysis by Country
10.1.2. Y-o-Y Growth Projections by Country
10.1.3. Latin America Average Pricing Analysis
10.2. Latin America Big Data Analytics in Tourism Market Size and Volume Forecast by Country
10.2.1. Brazil
10.2.2. Mexico
10.2.3. Rest of Latin America
10.3. Absolute $ Opportunity Assessment by Country
10.4. Latin America Big Data Analytics in Tourism Market Size and Volume Forecast by Application
10.4.1. Large Enterprises
10.4.2. SMEs
10.5. Basis Point Share (BPS) Analysis by Application
10.6. Y-o-Y Growth Projections by Application
10.7. Latin America Big Data Analytics in Tourism Market Size and Volume Forecast by Type
10.7.1. Structured
10.7.2. Semi-Structured
10.7.3. Unstructured
10.8. Basis Point Share (BPS) Analysis by Type
10.9. Y-o-Y Growth Projections by Type
10.10. Market Attractiveness/Growth Potential Analysis
10.10.1. By Country
10.10.2. By Product Type
10.10.3. By Application
10.10.4. By Sales Channel
10.11. Latin America Big Data Analytics in Tourism Demand Share Forecast, 2019-2026
11. Europe Big Data Analytics in Tourism Market Analysis and Forecast
11.1. Introduction
11.1.1. Basis Point Share (BPS) Analysis by Country
11.1.2. Y-o-Y Growth Projections by Country
11.1.3. Europe Average Pricing Analysis
11.2. Europe Big Data Analytics in Tourism Market Size and Volume Forecast by Country
11.2.1. Germany
11.2.2. France
11.2.3. Italy
11.2.4. U.K.
11.2.5. Spain
11.2.6. Russia
11.2.7. Rest of Europe
11.3. Absolute $ Opportunity Assessment by Country
11.4. Europe Big Data Analytics in Tourism Market Size and Volume Forecast by Application
11.4.1. Large Enterprises
11.4.2. SMEs
11.5. Basis Point Share (BPS) Analysis by Application
11.6. Y-o-Y Growth Projections by Application
11.7. Europe Big Data Analytics in Tourism Market Size and Volume Forecast by Type
11.7.1. Structured
11.7.2. Semi-Structured
11.7.3. Unstructured
11.8. BasisPoint Share (BPS) Analysis by Type
11.9. Y-o-Y Growth Projections by Type
11.10. Market Attractiveness/Growth Potential Analysis
11.10.1. By Country
11.10.2. By Product Type
11.10.3. By Application
11.10.4. By Sales Channel
11.11. Europe Big Data Analytics in Tourism Demand Share, 2019-2026
12. Asia Pacific Big Data Analytics in Tourism Market Analysis and Forecast
12.1. Introduction
12.1.1. Basis Point Share (BPS) Analysis by Country
12.1.2. Y-o-Y Growth Projections by Country
12.1.3. Asia Pacific Average Pricing Analysis
12.2. Asia Pacific Big Data Analytics in Tourism Market Size and Volume Forecast by Country
12.2.1. China
12.2.2. Japan
12.2.3. South Korea
12.2.4. India
12.2.5. Australia
12.2.6. Rest of Asia Pacific (APAC)
12.3. Absolute $ Opportunity Assessment by Country
12.4. Asia Pacific Big Data Analytics in Tourism Market Size and Volume Forecast by Application
12.4.1. Large Enterprises
12.4.2. SMEs
12.5. Basis Point Share (BPS) Analysis by Application
12.6. Y-o-Y Growth Projections by Application
12.7. Asia Pacific Big Data Analytics in Tourism Market Size and Volume Forecast by Type
12.7.1. Structured
12.7.2. Semi-Structured
12.7.3. Unstructured
12.8. Basis Point Share (BPS) Analysis by Type
12.9. Y-o-Y Growth Projections by Type
12.10. Market Attractiveness/Growth Potential Analysis
12.10.1. By Country
12.10.2. By Product Type
12.10.3. By Application
12.10.4. By Sales Channel
12.11. Asia Pacific Big Data Analytics in Tourism Demand Share, 2019-2026
13. Middle East & Africa Big Data Analytics in Tourism Market Analysis and Forecast
13.1. Introduction
13.1.1. Basis Point Share (BPS) Analysis by Country
13.1.2. Y-o-Y Growth Projections by Country
13.1.3. Asia Pacific Average Pricing Analysis
13.2. Middle East & Africa Big Data Analytics in Tourism Market Size and Volume Forecast by Country
13.2.1. Saudi Arabia
13.2.2. South Africa
13.2.3. UAE
13.2.4. Rest of Middle East & Africa (MEA)
13.3. Absolute $ Opportunity Assessment by Country
13.4. Middle East & Africa Big Data Analytics in Tourism Market Size and Volume Forecast by Application
13.4.1. Large Enterprises
13.4.2. SMEs
13.5. Basis Point Share (BPS) Analysis by Application
13.6. Y-o-Y Growth Projections by Application
13.7. Middle East & Africa Big Data Analytics in Tourism Market Size and Volume Forecast by Type
13.7.1. Structured
13.7.2. Semi-Structured
13.7.3. Unstructured
13.8. Basis Point Share (BPS) Analysis by Type
13.9. Y-o-Y Growth Projections by Type
13.10. Market Attractiveness/Growth Potential Analysis
13.10.1. By Country
13.10.2. By Product Type
13.10.3. By Application
13.10.4. By Sales Channel
13.11. Middle East & Africa Big Data Analytics in Tourism Demand Share, 2019-2026
14. Competition Landscape
14.1. Global Big Data Analytics in Tourism Market: Market Share Analysis
14.2. Big Data Analytics in Tourism Distributors and Customers
14.3. Big Data Analytics in Tourism Market: Competitive Dashboard
14.4. Company Profiles (Details Overview, Financials, Developments, Strategy)
14.4.1. Hewlett Packard Enterprise
14.4.1.1. Overview
14.4.1.2. Financials
14.4.1.3. Developments
14.4.1.4. Strategic Outlook
14.4.2. IBM
14.4.2.1. Overview
14.4.2.2. Financials
14.4.2.3. Developments
14.4.2.4. Strategic Outlook
14.4.3. Microsoft
14.4.3.1. Overview
14.4.3.2. Financials
14.4.3.3. Developments
14.4.3.4. Strategic Outlook
14.4.4. Oracle
14.4.4.1. Overview
14.4.4.2. Financials
14.4.4.3. Developments
14.4.4.4. Strategic Outlook
14.4.5. Hitachi
14.4.5.1. Overview
14.4.5.2. Financials
14.4.5.3. Developments
14.4.5.4. Strategic Outlook
14.4.6. SAP
14.4.6.1. Overview
14.4.6.2. Financials
14.4.6.3. Developments
14.4.6.4. Strategic Outlook
14.4.7. Google
14.4.7.1. Overview
14.4.7.2. Financials
14.4.7.3. Developments
14.4.7.4. Strategic Outlook
14.4.8. Amazon
14.4.8.1. Overview
14.4.8.2. Financials
14.4.8.3. Developments
14.4.8.4. Strategic Outlook
14.4.9. Accenture
14.4.9.1. Overview
14.4.9.2. Financials
14.4.9.3. Developments
14.4.9.4. Strategic Outlook
14.4.10. TIBCO
14.4.10.1. Overview
14.4.10.2. Financials
14.4.10.3. Developments
14.4.10.4. Strategic Outlook
14.4.11. Tableau
14.4.11.1. Overview
14.4.11.2. Financials
14.4.11.3. Developments
14.4.11.4. Strategic Outlook
14.4.12. COMPANY 12
14.4.12.1. Overview
14.4.12.2. Financials
14.4.12.3. Developments
14.4.12.4. Strategic Outlook
14.4.13. COMPANY 13
14.4.13.1. Overview
14.4.13.2. Financials
14.4.13.3. Developments
14.4.13.4. Strategic Outlook
14.4.14. COMPANY 14
14.4.14.1. Overview
14.4.14.2. Financials
14.4.14.3. Developments
14.4.14.4. Strategic Outlook
14.4.15. COMPANY 15
14.4.15.1. Overview
14.4.15.2. Financials
14.4.15.3. Developments
14.4.15.4. Strategic Outlook
14.4.16. COMPANY 16
14.4.16.1. Overview
14.4.16.2. Financials
14.4.16.3. Developments
14.4.16.4. Strategic Outlook
14.4.17. COMPANY 17
14.4.17.1. Overview
14.4.17.2. Financials
14.4.17.3. Developments
14.4.17.4. Strategic Outlook
14.4.18. COMPANY 18
14.4.18.1. Overview
14.4.18.2. Financials
14.4.18.3. Developments
14.4.18.4. Strategic Outlook
14.4.19. COMPANY 19
14.4.19.1. Overview
14.4.19.2. Financials
14.4.19.3. Developments
14.4.19.4. Strategic Outlook
14.4.20. COMPANY 20
14.4.20.1. Overview
14.4.20.2. Financials
14.4.20.3. Developments
14.4.20.4. Strategic Outlook
