Asia Pacific Big Data In E-commerce Market Forecast 2020-2028

Asia Pacific Big Data In E-commerce Market Forecast 2020-2028

The Asia Pacific big data in e-commerce market is evaluated to showcase growth, registering a CAGR of 15.10% during the forecast period, 2020-2028. The growing online product search and social platforms for e-shopping, the increasing digital connectivity, and the rising internet penetration rate are the factors estimated to propel the growth of the market.

The countries included for assessing the growth of the Asia Pacific big data in e-commerce market are Thailand, Vietnam, India, China, Australia & New Zealand, Indonesia, South Korea, Japan, and the rest of Asia Pacific. There have been significant investments in terms of big data adoption in Japan. The new IT strategy of Japan prioritizes open public data and big data. Ryohin Keikaku Co. Ltd. incorporated InteractEdge from Infosys for generating higher sales through personalized product recommendations. South Korea is witnessing rapid growth in its mature e-commerce market, due to the increasing retail sales online and the growing number of mobile devices. The government also aims to build a big data platform that involves the blockchain so as to allow data management security and boost the sharing economy. With the growing number of people getting connected to the internet, the big data implementation in Indonesia is estimated to grow at a faster pace. The country also boasts of a fast-paced economy. The cloud based deployments in the Asia Pacific region have grown significantly, since the businesses are transitioning from simple back-end operations to core processes, which add to the overall growth aspects of the market.

Some of the key companies influencing the revenue growth of the market are International Business Machines Corporation (IBM), Hewlett Packard Enterprise Company, Guavus Inc, Microsoft Corporation, Hitachi Ltd, etc.

Our report offerings include:
• Explore key findings of the overall market
• Strategic breakdown of market dynamics (Drivers, Restraints, Opportunities, Challenges)
• Market forecasts for a minimum of 9 years, along with 3 years of historical data for all segments, sub-segments, and regions
• Market Segmentation cater to a thorough assessment of key segments with their market estimations
• Geographical Analysis: Assessments of the mentioned regions and country-level segments with their market share
• Key analytics: Porter's Five Forces Analysis, Vendor Landscape, Opportunity Matrix, Key Buying Criteria, etc.
• Competitive landscape is the theoretical explanation of the key companies based on factors, market share, etc.
• Company profiling: A detailed company overview, product/services offered, SCOT analysis, and recent strategic developments

1. Research Scope & Methodology
1.1. Study Objectives
1.2. Scope Of Study
1.3. Methodology
1.4. Assumptions & Limitations
2. Executive Summary
2.1. Market Size & Estimates
2.2. Market Overview
3. Market Dynamics
3.1. Parent Market Analysis: Big Data Market
3.2. Development Of Big Data
3.3. Market Definition
3.4. Key Drivers
3.4.1. Utilization Of Big Data For Improving Sales & Customer Satisfaction
3.4.2. Use Of Big Data By E-commerce Companies To Drive Product Customizations
3.4.3. Growing Inclination Towards Various Online Payment Methods
3.5. Key Restraints
3.5.1. Shortage Of Trained Big Data Experts
3.5.2. Concerns Related To Data Accuracy & Privacy
4. Key Analytics
4.1. Key Investment Insights
4.2. Porter’s Five Force Analysis
4.2.1. Buyer Power
4.2.2. Supplier Power
4.2.3. Substitution
4.2.4. New Entrants
4.2.5. Industry Rivalry
4.3. Opportunity Matrix
4.4. Vendor Landscape
4.5. Value Chain Analysis
5. Market By Component
5.1. Software
5.2. Hardware
6. Market By Deployment Model
6.1. Cloud Based
6.1.1. Private Cloud
6.1.2. Public Cloud
6.2. On-premises
7. Market By Type
7.1. Structured
7.2. Unstructured
7.3. Semi-structured
8. Market By Solution
8.1. Content Analytics
8.2. Customer Analytics
8.3. Fraud Detection
8.4. Risk Management
9. Market By End-user
9.1. Online Classified
9.2. Online Education
9.3. Online Financial
9.3.1. Banking Services/Wallets
9.3.2. Financial Services
9.4. Online Retail
9.5. Online Travel And Leisure
9.6. Other End-users
10. Geographical Analysis
10.1. Asia Pacific
10.1.1. China
10.1.2. Japan
10.1.3. India
10.1.4. South Korea
10.1.5. Indonesia
10.1.6. Thailand
10.1.7. Vietnam
10.1.8. Australia & New Zealand
10.1.9. Rest Of Asia Pacific
11. Company Profiles
11.1. Amazon Web Services Inc
11.2. Cloudera Inc
11.3. Data Usa
11.4. Dell Inc
11.5. Guavus Inc
11.6. Hewlett Packard Enterprise Company
11.7. Hitachi Ltd
11.8. International Business Machines Corporation (Ibm)
11.9. Microsoft Corporation
11.10. Oracle Corporation
11.11. Palantir Technologies
11.12. Sap Se
11.13. Sas Institute
11.14. Splunk Inc
11.15. Teradata Corporation

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