Universal data analysis rules, master the essence of analytical thinking, and be proficient in multiple types of business scenarios
| Universal data analysis rules, master the essence of analytical thinking, and be proficient in multiple types of business scenarios. Resource introduction: Universal data analysis rules, master the essence of analytical thinking, and be proficient in multiple types of business scenarios. In the era of big data, data analysis is an increasingly valued skill. How to conduct effective analysis in different industries and business scenarios? What is examined is the practitioner's data analysis thinking, that is, the ability to use data analysis skills. Having the right data analysis mindset will not only allow you to handle various types of analysis needs with ease, but also make your work more efficient. Course Catalog [5870] Opening words Skills determine the lower limit, thinking determines the upper limit.md [5871] 01 Goal-oriented: How to get out of the vicious circle of data acquisition? .md [5872] 02 Objectivity and rigor: facts + argumentation process + opinions to create high-level analysis.md [5873] 03 Indicator thinking: How to understand the various types of indicators.md [5874] 04 Logical reasoning: What does the logical thinking ability in the recruitment requirements refer to? .md [5875] 05 System structure: Look at the problem from a perspective beyond the problem itself and let your analysis get to the point.md [5876] 06 Understand the business: Make sure your analysis results are in sync with the business side and leadership.md [5877] 07 Understand the user: Data analysis + user thinking = refined operations.md [5878] 08 Analysis process: General process for business data analysis.md [5879] 09 Define the problem: How to define the problem and open up analytical thinking? .md [5880] 10 Disassembly question: Why is a bunch of useless data always disassembled? .md [5881] 11 Find out the cause: There are so many causes of the problem, which one is the most critical.md [5882] 12 Make suggestions: What are valuable suggestions? .md [5883] 13 Report Writing: How to write a data analysis report efficiently? .md [5884] 14 Advanced analysis framework: other common analysis processes (mathematical modeling for predicting competitor users).md [5885] 15 Product analysis: How to increase the next-day retention rate of a certain function by 10%? .md [5886] 16 Conversion analysis: How to improve product purchase conversion rate? .md [5887] 17 Activity analysis: How to analyze activity effects and give effective suggestions? .md [5888] 18 User growth: Identify key behaviors that quickly increase the number of users.md [5889] 19 AB testing: Evaluate and optimize the effectiveness of AB testing.md [5890] Easter egg 1 Data operation: How to build a data operation system? .md [5891] Easter Egg 2 Interview: Interview Guide for Business Data Analysts.md [5892] Conclusion: In-depth business and continuous learning.md Document [5870] Opening words: Skills determine the lower limit, and thinking determines the upper limit.mp4 [5871] 01 Goal-oriented: How to get out of the vicious circle of data acquisition? .mp4 [5872] 02 Objectivity and rigor: facts + argumentation process + opinions to create high-level analysis.mp4 [5873] 03 Indicator thinking: How to understand the various types of indicators.mp4 [5874] 04 Logical reasoning: What does the logical thinking ability in the recruitment requirements mean? .mp4 [5875] 05 System structure: Look at the problem from a different perspective and let your analysis get to the point.mp4 [5876] 06 Understand the business: Make sure your analysis results are in sync with the business side and leadership.mp4 [5877] 07 Understand the user: Data analysis + user thinking = refined operations.mp4 [5878] 08 Analysis process: General process of business data analysis.mp4 [5879] 09 Define the problem: How to define the problem and open up analytical thinking? .mp4 [5880] 10 Disassembly question: Why is a bunch of useless data always disassembled? .mp4 [5881] 11 Find out the cause: There are so many causes of the problem, which one is the most critical one.mp4 [5882] 12 Make suggestions: What are valuable suggestions? .mp4 [5883] 13 Report Writing: How to write a data analysis report efficiently? .mp4 [5884] 14 Advanced analysis framework: other common analysis processes (mathematical modeling for predicting competitor users).mp4 [5885] 15 Product analysis: How to increase the next-day retention rate of a certain function by 10%? .mp4 [5886] 16 Conversion analysis: How to improve product purchase conversion rate? .mp4 [5887] 17 Activity Analysis: How to analyze activity effects and provide effective suggestions? .mp4 [5888] 18 User growth: Identify key behaviors that quickly increase the number of users.mp4 [5889] 19 AB testing: Evaluating and optimizing the effectiveness of AB testing.mp4 [5890] Easter egg 1 Data operation: How to build a data operation system? .mp4 [5891] Easter Egg 2 Interview: Interview Guide for Business Data Analysts.mp4 [5892] Conclusion: In-depth understanding of business and continuous learning.mp4 |
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