Big data thinking includes?

1.Data-driven: big data thinking believes that data is the basis for decision-making, and through the collection, analysis and processing of large amounts of data, valuable information can be mined to provide a basis for decision-making.

2. Holistic concept: Big data thinking emphasizes that the whole is greater than the sum of its parts, and that only by integrating and analyzing data from different fields can new patterns and opportunities be discovered.

3. Relevance thinking: Instead of pursuing causality, big data thinking focuses on the correlation between data. By discovering the correlation between data, future trends and behaviors can be better predicted.

4. Predictive ability: Big data thinking believes that future trends and behaviors can be predicted by mining and analyzing historical data. This predictive ability is highly valuable in areas such as finance, healthcare, and marketing.

5. Amount of precision: Big data thinking emphasizes the amount of precision of things, through the quantitative analysis of data, you can more accurately understand the nature and laws of things.

6. Agile Response: Big Data Thinking believes that the world is dynamically changing and that data needs to be collected and analyzed in real time in order to respond quickly to market changes and customer needs.

7. Open Source Thinking: Big Data Thinking encourages openness and ****enjoyment, believing that openness and ****enjoyment of data can promote innovation and progress. The development of open source communities is the embodiment of big data thinking in practice.

8. Information security: big data thinking recognizes the value and sensitivity of data, so when processing and using data, information security and personal privacy protection should be fully considered.