What role does exploratory data analysis (EDA) play in a data analysis project, and what are some commonly used EDA techniques?
How can data visualization be used to enhance the understanding of data analysis results and communicate insights to stakeholders?
What are some common challenges encountered during data cleaning, and what strategies can be used to address them effectively?
How do you determine which data analysis techniques are most appropriate for a given dataset and business problem?
What are the key steps involved in the data analysis process, and how can each step be effectively implemented to ensure accurate results?
5. **What are some common data visualization techniques used to effectively communicate insights derived from data analysis?
4. **How do you select the appropriate statistical methods or machine learning algorithms for a given data analysis problem?
3. **What are the key performance indicators (KPIs) to consider when evaluating the effectiveness of a data analysis model?
2. **How can you handle missing or incomplete data in a dataset to ensure accurate analysis?
**What is the difference between structured and unstructured data, and how does it impact data analysis techniques?
