What CDA data analysts need to learn includes, but is not limited to:
1. Fundamentals of Statistics: including descriptive statistics, inferential statistics, probability theory and mathematical statistics.
2. Data cleaning and sorting: master the skills of data cleaning, data integration, data format conversion, etc.
3. Data analysis tools: learn to use data analysis tools such as Excel, Python, R, etc., for data analysis and modeling.
4. Data visualization: Learn how to use tools to visualize data, such as making charts, data maps, etc.
5. Database knowledge: understand the basic concepts of databases, such as relational databases, non-relational databases, etc.
6. Data mining and machine learning: learn to use algorithms for classification, clustering, and other tasks.
7. Business knowledge: understand the business background and data characteristics of different industries, such as finance, e-commerce, medical care, etc.
8. Data analysis report writing: learn how to write concise, clear and logical data analysis reports, and be able to explain and present data analysis results to business personnel or decision makers.
9. Data ethics and privacy protection: understand the laws and regulations on data ethics and privacy protection, and master how to protect user privacy in the process of data analysis.
10. Practical project experience: accumulate practical experience and improve the ability to solve practical problems by participating in actual projects.
The above content is for reference only, and the specific learning content can be selected according to personal interests and career development direction. At the same time, it is recommended to continue to pay attention to the latest developments and tools in the field of data analysis, and constantly improve your skills and knowledge level.