Common patterns and methods of big data thinking include

Common patterns and methods of big data thinking include:

1. data collection and cleaning: collect a large amount of data, clean and preprocess the data to ensure the accuracy and integrity of the data.

2. Data storage and management: Choose appropriate data storage and management technologies, such as distributed file system and database, in order to effectively store and manage a large amount of data.

3. Data analysis and mining: Use various data analysis and mining technologies, such as statistical analysis, machine learning and data visualization, to extract valuable information and insights from big data.

4. Data models and forecasts: Establish appropriate data models and use these models for forecasting and decision support to help enterprises make more accurate decisions.

5. Data security and privacy protection: Ensure the security and privacy protection of big data, and take appropriate security measures, such as data encryption and access control.