What are the application fields of big data?

Big data is widely used, covering many different industries and fields. The following are some major big data application fields, some practical application examples in various fields and common application platforms in China:

I. Application fields and examples

1, Business and Marketing:

Market analysis and trend prediction: By analyzing a large number of market data, such as sales data and consumer behavior, we can predict production demand and market trends and help enterprises adjust their marketing strategies.

Personalized marketing: Use big data analysis to realize personalized advertising and recommendation according to consumers' purchase history and preferences, and improve sales conversion rate.

Pricing optimization: By analyzing the data of competitors' prices and consumers' responses, we can optimize the product pricing strategy and maximize profits.

Example: Amazon's personalized recommendation system: Amazon provides personalized product recommendations for each user by analyzing the user's purchase history, browsing records and clicks, thus improving the purchase conversion rate and customer satisfaction.

2. Finance and banking:

Risk management: use big data analysis to predict the borrower's default risk and help banks reduce loan losses.

Investment decision: by analyzing market data and economic indicators, etc. To help investors make more informed investment decisions.

High-frequency trading: use big data analysis to conduct high-frequency trading and adjust trading strategies in real time according to market changes.

For example: credit card fraud detection: financial institutions use big data to analyze customers' transaction and behavior patterns and detect abnormal transaction patterns, so as to find credit card fraud in time.

3, medical care:

Personalized medical treatment: analyze the patient's genome data, medical records and other information, formulate personalized treatment programs, and improve the treatment effect.

Disease prediction: By analyzing the data of disease transmission and patients' visits, predict the outbreak and spread trend of diseases.

Drug research and development: analyze data such as molecular structure and drug interaction to accelerate the process of drug research and development.

For example, genomics research: researchers use big data to analyze large-scale genome data, understand the relationship between genes and diseases, and provide support for personalized medical care and drug research and development.

4. Manufacturing industry:

Supply chain optimization: by analyzing supply chain data, optimize production planning, inventory management and logistics, and improve production efficiency.

Equipment maintenance prediction: Through the sensor data, the equipment failure can be predicted, and the production interruption time and maintenance cost can be reduced.

For example: quality control: sensor data used by manufacturing industry, production process data, etc. Analyze the changes and anomalies in the production line, so as to realize real-time quality monitoring and defect prediction.

5. Energy and public utilities:

Energy consumption optimization: analyze energy usage data, optimize energy consumption and reduce energy waste.

Smart grid management: By analyzing grid data and monitoring power supply, more reliable power supply can be achieved.

Example: Smart meters: Smart meters can help energy companies better understand energy consumption and make more reasonable power supply plans by recording energy use patterns.

6. Transportation and logistics:

Traffic flow management: By analyzing traffic data, optimize traffic lights and road planning to reduce traffic congestion.

Logistics optimization: analyze logistics data, optimize the route and time of goods transportation, and reduce logistics costs.

Example: Uber's dynamic pricing: Uber uses big data to analyze real-time traffic conditions and passenger demand, adjust fares, realize dynamic pricing, and provide more accurate ride services.

7. Social media and the Internet:

User behavior analysis: analyze users' behaviors and interactions on social media, understand users' interests and preferences, and improve user experience.

Emotional analysis: Analyze social media content, understand the public's feelings and attitudes, and use it for public opinion analysis and brand management.

For example: Twitter public opinion analysis: analyzing a large number of user tweets on Twitter can help us understand the public's feelings and attitudes towards specific events, products or topics, and can be used for public opinion analysis and brand management.

8. Agriculture:

Crop management: Optimize crop planting and management strategies by analyzing meteorological data and soil data.

Precision agriculture: the application of sensor data to achieve precision fertilization, irrigation and pesticide use, and improve crop yield.

Example: Meteorological data analysis: Meteorological data is used in agriculture to make predictions, helping farmers to arrange crop planting time and irrigation plan reasonably, thus improving crop yield and quality.

Second, domestic big data application platforms and tools:

Big data computing platforms: JDPresto in jingdong cloud, MaxCompute in Alibaba Cloud and Elastic MapReduce in Tencent Cloud are also common in China.

Database: There are also some big data database solutions in China, such as TiDB of PingCAP, GaussDB of Huawei and AnalyticDB of Alibaba Cloud.

Alibaba Cloud: Alibaba Cloud also provides a wealth of big data platforms, including MaxCompute, DataWorks and AnalyticDB.

Baidu AI Cloud: Baidu AI Cloud provides big data computing and storage services such as BDS (Baidu Distributed Service) and BIE (Baidu Intelligent Big Data Computing Engine).

Jingdong cloud: jingdong cloud has provided JDPresto, a big data analysis platform, and JD Data Warehouse, a data warehouse service.

Kaggle: a world-renowned data science competition platform, which provides various data mining and machine learning competition tasks, and is participated by data scientists and machine learning practitioners.

DataCastle: China data science competition platform, affiliated to Chengdu Juju Castle Technology Co., Ltd., is a data geek circle founded by Professor Zhou Tao of University of Electronic Science and Technology of China, which brings together global data elites, leading data science thinking and wisdom, and high-quality data resources from various industries.

DrivenData: a data science competition platform dedicated to social issues, encouraging data scientists to solve important problems in the world.

CodaLab: Provide various machine learning and computing competitions to support challenges in many fields.

CrowdANALYTIX: provides data science competitions and projects covering many industries and application fields.