1. Data collection: collecting big data, including structured and unstructured data, and the collected data can come from external sources or internal data sources;
2. Data storage: storing the collected data in reliable data warehouses in order to better manage the data;
3. data processing: cleaning, structuring and standardizing the collected data in order to get useful information from it;
4. data analytics: mining the data with big data analytics tools in order to discover useful information and patterns.
Expansion:
5. Data visualization: using data visualization techniques to graphically display the processed data in order to analyze the data more intuitively;
6. Result sharing: sharing the results of the processing through reports and other forms, so that more people can be involved in the data processing process.