Investment Opportunities of Big Data Technology in China (2016 - 2021)

  • ID: 3970921
  • Report
  • Region: China
  • 122 pages
  • Mordor Intelligence
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Big Data, which refers to the gigantic volume of dynamic data, is characterised by its volume, variety, velocity and value. The technology with fundamental components such as basic infrastructure, data organization and management, analytics and data mining and decision support system and process automation system, has been growing at a CAGR of 35% from 2015 to 2020. The Big Data market in China consists of storage, server, networking, analytics software and application, and services market.

Though China has the third largest rate of adoption of big data technology after U.S and India, the technology is predominant in IT domain followed by consumer-centric verticals like retail and e-commerce. The technology is fairly nascent in healthcare and pharmaceutical vertical as well as in Governmental organizations. China generates an immense amount of data from various sources, and if put to proper storage and analysis, the data can generate some valuable trends and insights into the behaviour of the customer and will help make more informed decisions in real-time.

The primary drivers of the technology in China are the explosion of data due to rising rates of internet, mobile/smartphone penetration, advancement in algorithm development and machine learning, and the need for customer and behavioural analytics. The economy has also lately been supported by the Government of China. The Government is encouraging investment in the infrastructure required for the storage and analysis of big data in the domestic market.

The market can be segmented on the basis of deployment (On-Premise and Cloud), approach (Hadoop, NoSQL, MPAD and others) and verticals (Telecom and IT, Financial Services, Energy and Power, Retail, Tourism, Manufacturing, Engineering and Construction, Aerospace and Defense, Media and Entertainment, Healthcare and others) with sub-verticals on the basis of particular applications.

Meanwhile, leading Chinese firms from the domain of e-commerce, banking and telecom etc. have started incorporating data analytics for more strategic functioning, smoother operations and more efficient management.

Alibaba, Baidu and Tencent have recently begun to make large investments in e-commerce, finance, and data mining and analytics. Other prominent companies in this domain are Asia Analytics (formerly known as SPSS China), Traintracks and Comrise. This report concentrates on certain key business parameters, indicating the robustness and the company's potential to invest in, such as the Current Sales Figure, Cash Flow Statements, Annual Turnover, Profit and Loss Statement CAGR, Patents, Legal Issues etc. Global Giants in the IT market such as IBM, Microsoft, Oracle, SAP, Cisco and SAS have invested heavily in establishing data centres in China, developing services and acquiring software companies that specialize in business intelligence tools.

However, the technology has more scope of applicability and adoption in China and shows tremendous promise as most Chinese companies do not own enough data and still lack the technical expertise to utilize analyse and monetize this data.

What the report offers

1. Market Definition and an in-depth analysis for the Big Data market in China along with identification of key drivers and restraints for the market.

2. Identification of factors instrumental in changing the market scenarios, rising prospective opportunities and identification of key companies which can influence the market on a regional and country scale.

3. Extensively researched competitive landscape section with profiles of emerging companies along with their financials, asset and liability account, strategic initiatives and market shares.

4. Identification and analysis of the Macro and Micro factors that affect the Big Data Analytics Market of the China market.

Please note: As this product is updated at the time of order, dispatch will be 72 hours from the date the order and full payment is received.
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1. Introduction

1.1 Big Data technology

1.2 Charecteristics of Big Data

1.2.1 Volume

1.2.2 Variety

1.2.3 Velocity

1.2.4 Value

1.3 Big Data Adoption

1.4 Role of Big Data in Business Units

1.4.1 Marketing

1.4.2 Operations

1.4.3 IT

1.4.4 Sales

1.4.5 Finance

1.4.6 Others

2. Scope of Report

3. Market Overview

3.1 Introduction

3.2 Supply-Side Analysis

3.3 Demand-Side Anaysis

3.4 Porter's Five Industry Forces Analysis

3.4.1 Industry competition

3.4.2 Potential of new entrants

3.4.3 Power of suppliers

3.4.4 Power of customers

3.4.5 Threat of substitute products

3.5 PESTEL Analysis

3.5.1 Political Factors

3.5.2 Economical Factors

3.5.3 Social Factors

3.5.4 Technological Factors

3.5.5 Environmental Factors

3.5.6 Legal Factors

3.6 Market Regulations and Policies

4. Market Dynamics

4.1 Drivers

4.1.1 Rising Rates of Internet and Mobile Penetration

4.1.2 Data Explosion: Unstructure, Semi-structured and Complex

4.1.3 Improvement in Algorithm Development

4.1.4 Need for Customer Analytics

4.1.5 Fast Growing Urban Economy

4.2 Restraints

4.2.1 Organizational Barriers and Industry Structures

4.2.2 Budget Restrictions

4.2.3 Data Security Concerns

4.2.4 Governmental Regulations

4.2.5 Stiff Competition

4.3 Opportunities

4.3.1 Supply Side Business Opportunities

4.3.1.1 E-commerce

4.3.1.2 Analytics Software

4.3.1.3 Outsourcing, Hosting and as-a-service Offering

4.3.1.4 Consulting

4.3.1.5 Enhanced Customer Support

4.3.2 Demand-Side Business Opportunities

4.3.2.1 Information access

4.3.2.2 Analytics Sofware

4.3.2.3 Operations

5. Market Segmentation

5.1 By Deployment

5.1.1 On-Premise

5.1.2 Cloud

5.2 By Approach

5.2.1 Hadoop

5.2.2 NoSQL

5.2.3 MPAD (Massively Parallel Analytic Databases)

5.2.4 Others and Analytic Technologies

5.3 By Vertical

5.3.1 Telecom and IT

5.3.1.1 Location Based Services

5.3.1.2 Customer Churn Prevention

5.3.2 Energy and Power

5.3.2.1 Optimizing Energy Production

5.3.2.2 Forcasting Energy

5.3.2.3 Exploration and Identification of Wells and Mines

5.3.2.4 Drilling Potential Maximization

5.3.2.5 Billing Analytics

5.3.2.5.1 Predictive Maintanance

5.3.2.5.2 Turbine Placement Optimization

5.3.3 Financial Services

5.3.3.1 Customer Retention

5.3.3.2 Personalized Product Offering

5.3.3.3 Risk Management

5.3.3.4 Credit Scoring

5.3.3.5 Fraud Prevention and Detection

5.3.3.6 Insurance Analytics

5.3.3.6.1 Customer Retention and Profiling

5.3.3.6.2 Fraud Mitigation

5.3.3.6.3 Risk Management

5.3.3.7 Economic Analysis

5.3.3.8 Business Intelligence

5.3.4 Retail

5.3.4.1 Sales Analytics

5.3.4.2 Supply Chain Monitoring

5.3.4.3 Personalized Marketing

5.3.4.4 Price Optimization

5.3.4.5 Customer Sentiment Analysis

5.3.4.6 Customer Retention

5.3.5 Tourism

5.3.6 Manufacturing

5.3.6.1 Asset Management

5.3.6.2 Quality Analytics

5.3.6.3 Environemental Impact Assessment

5.3.7 Professional Services

5.3.8 Transportation and Logistics

5.3.8.1 Predictive Warranty Analysis

5.3.8.2 Traffic Control

5.3.8.3 Transport Fleet Optimization

5.3.8.4 Urban Transportation Management

5.3.9 Aerospace and Defense

5.3.9.1 Predictive Warranty Analysis

5.3.9.2 Air Traffic Control

5.3.9.3 Predictive Airport Maintenance and Fuel Optimization

5.3.9.4 Intelligent Gathering

5.3.9.5 Injury Prevention and Mitigation

5.3.9.6 Energy Savings in Battlefield

5.3.10 Media and Entertainment

5.3.10.1 Channel Optimization

5.3.10.2 Optimized Search Engine

5.3.10.3 Recommended Engines

5.3.11 Engineering and Construction

5.3.11.1 Information Integration

5.3.11.2 Identifying and Learning Patterns

5.3.11.3 Energy Optimization

5.3.11.4 Fault Detection

5.3.11.5 Intelligent Home Analytics

5.3.11.6 Water Management

5.3.11.7 Urban Waste Management

5.3.12 Healthcare and Pharmaceuticals

5.3.12.1 Health Efficiency

5.3.12.2 Medical Data Analytics

5.3.13 Others

5.3.14 Emerging Big Data Companies in China

5.3.14.1 Baidu

5.3.14.2 Current Sales Figure

5.3.14.3 Cash Flow Statements

5.3.14.4 Annual Turnover

5.3.14.5 Profit and Loss Statement

5.3.14.6 Net worth

5.3.14.7 Debt

5.3.14.8 CAGR

5.3.14.9 New and Existing Contracts

5.3.14.10 Recent Fundings

5.3.14.11 Basic Financial Structure

5.3.14.12 Patents

5.3.14.13 Product and Service Features

5.3.14.14 Recent Technologies

5.3.14.15 Number of Employees

5.3.14.16 Market Presence

5.3.14.17 Client List

5.3.14.18 Sales Forecast

5.3.14.19 Return on Investment

5.3.14.20 Legal Information

5.3.14.21 Company Goodwill

5.3.14.22 Funding Pattern

5.3.15 Major Investors

5.3.15.1 Alibaba

5.3.15.2 Current Sales Figure

5.3.15.3 Cash Flow Statements

5.3.15.4 Annual Turnover

5.3.15.5 Profit and Loss Statement

5.3.15.6 Net worth

5.3.15.7 Debt

5.3.15.8 CAGR

5.3.15.9 New and Existing Contracts

5.3.15.10 Recent Fundings

5.3.15.11 Basic Financial Structure

5.3.15.12 Patents

5.3.15.13 Product and Service Features

5.3.15.14 Recent Technologies

5.3.15.15 Number of Employees

5.3.15.16 Market Presence

5.3.15.17 Client List

5.3.15.18 Sales Forecast

5.3.15.19 Return on Investment

5.3.15.20 Legal Information

5.3.15.21 Company Goodwill

5.3.15.22 Funding Pattern

5.3.16 Major Investors

5.3.16.1 Tencent

5.3.16.2 Current Sales Figure

5.3.16.3 Cash Flow Statements

5.3.16.4 Annual Turnover

5.3.16.5 Profit and Loss Statement

5.3.16.6 Net worth

5.3.16.7 Debt

5.3.16.8 CAGR

5.3.16.9 New and Existing Contracts

5.3.16.10 Recent Fundings

5.3.16.11 Basic Financial Structure

5.3.16.12 Patents

5.3.16.13 Product and Service Features

5.3.16.14 Recent Technologies

5.3.16.15 Number of Employees

5.3.16.16 Market Presence

5.3.16.17 Client List

5.3.16.18 Sales Forecast

5.3.16.19 Return on Investment

5.3.16.20 Legal Information

5.3.16.21 Company Goodwill

5.3.16.22 Funding Pattern

5.3.17 Major Investors

5.3.17.1 Asia Analytics (Formerly SPSS China)

5.3.17.2 Current Sales Figure

5.3.17.3 Cash Flow Statements

5.3.17.4 Annual Turnover

5.3.17.5 Profit and Loss Statement

5.3.17.6 Net worth

5.3.17.7 Debt

5.3.17.8 CAGR

5.3.17.9 New and Existing Contracts

5.3.17.10 Recent Fundings

5.3.17.11 Basic Financial Structure

5.3.17.12 Patents

5.3.17.13 Product and Service Features

5.3.17.14 Recent Technologies

5.3.17.15 Number of Employees

5.3.17.16 Market Presence

5.3.17.17 Client List

5.3.17.18 Sales Forecast

5.3.17.19 Return on Investment

5.3.17.20 Legal Information

5.3.17.21 Company Goodwill

5.3.17.22 Funding Pattern

5.3.18 Major Investors

5.3.18.1 Traintracks

5.3.18.2 Current Sales Figure

5.3.18.3 Cash Flow Statements

5.3.18.4 Annual Turnover

5.3.18.5 Profit and Loss Statement

5.3.18.6 Net worth

5.3.18.7 Debt

5.3.18.8 CAGR

5.3.18.9 New and Existing Contracts

5.3.18.10 Recent Fundings

5.3.18.11 Basic Financial Structure

5.3.18.12 Patents

5.3.18.13 Product and Service Features

5.3.18.14 Recent Technologies

5.3.18.15 Number of Employees

5.3.18.16 Market Presence

5.3.18.17 Client List

5.3.18.18 Sales Forecast

5.3.18.19 Return on Investment

5.3.18.20 Legal Information

5.3.18.21 Company Goodwill

5.3.18.22 Funding Pattern

5.3.19 Major Investors

5.3.19.1 Comrise

5.3.19.2 Current Sales Figure

5.3.19.3 Cash Flow Statements

5.3.19.4 Annual Turnover

5.3.19.5 Profit and Loss Statement

5.3.19.6 Net worth

5.3.19.7 Debt

5.3.19.8 CAGR

5.3.19.9 New and Existing Contracts

5.3.19.10 Recent Fundings

5.3.19.11 Basic Financial Structure

5.3.19.12 Patents

5.3.19.13 Product and Service Features

5.3.19.14 Recent Technologies

5.3.19.15 Number of Employees

5.3.19.16 Market Presence

5.3.19.17 Client List

5.3.19.18 Sales Forecast

5.3.19.19 Return on Investment

5.3.19.20 Legal Information

5.3.19.21 Company Goodwill

5.3.19.22 Funding Pattern

6. Major Investors

7. Market Landscape

7.1 Market Trends

7.2 Market Forecasts

7.3 New Product Development and Innovations

7.4 Mergers and Acquisitions
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