5. **What role does data visualization play in data analysis, and what are some effective techniques for presenting data insights to stakeholders?
4. **How do you choose the right statistical methods and tools for a specific data analysis project, and what factors influence this decision?
3. **What is the difference between descriptive, diagnostic, predictive, and prescriptive analytics, and when is each type most appropriately used?
2. **How do you handle missing or incomplete data during analysis, and what are the best practices for ensuring data quality and integrity?
**What are the key steps involved in the data analysis process, and how do they contribute to generating insights?
5. **What role does data cleaning and preprocessing play in the data analysis process, and what are some common techniques used to prepare data for analysis?
4. **How can you handle missing or incomplete data during analysis to ensure accurate and reliable results?
3. **What are some common data visualization techniques, and how can they help in interpreting and presenting data analysis results?
2. **How do descriptive statistics differ from inferential statistics, and how are each used in data analysis?
**What are the key steps involved in the data analysis process, and how can each step impact the overall analysis?