What role do statistical techniques play in data analysis, and how can they be used to uncover insights and trends within a data set?
How can data quality and integrity impact the results of data analysis, and what strategies can be implemented to ensure high-quality data?
What are the main differences between descriptive, predictive, and prescriptive analytics, and how can each be applied to solve real-world problems?
How can data visualization techniques enhance the interpretation of complex data sets in a business context?
What are the key steps involved in the data analysis process, and how do they contribute to making data-driven decisions?
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?