Internshala Associate Data Analyst Interview Questions, Process, and Tips

Left Join is a type of join operation in SQL that returns all rows from the left table and the matched rows from the right table.

• Left Join combines rows from two tables based on a related column between them.

• It includes all rows from the left table, even if there are no matches in the right table.

• If there are no matches, NULL values are included for columns from the right table.

• Example: SELECT * FROM table1 LEFT JOIN t

SQL queries are executed in a specific order to ensure accurate results.

• SQL queries are executed in the following order: FROM, WHERE, GROUP BY, HAVING, SELECT, ORDER BY.

• The FROM clause specifies the tables involved in the query.

• The WHERE clause filters the rows based on specified conditions.

• The GROUP BY clause groups the rows based on specified columns.

• The HAVING clause filters the grouped rows based on specified condi...read more

Developed a predictive analytics model for customer churn in a telecom company.

• Collected and cleaned customer data from various sources

• Performed exploratory data analysis to identify patterns and trends

• Built a machine learning model to predict customer churn

• Evaluated the model's performance using metrics like accuracy and precision

• Provided actionable insights to reduce customer churn rate

I took a structured approach by first defining the problem, collecting relevant data, analyzing the data, and then presenting findings.

• Defined the problem statement clearly to understand the scope of analysis

• Collected relevant data from various sources such as databases, surveys, and external research

• Analyzed the data using statistical tools and techniques to derive insights

• Presented findings in a clear and concise man

I have experience with various machine learning models such as linear regression, decision trees, random forests, and neural networks.

• Linear regression is used for predicting continuous outcomes.

• Decision trees are used for classification and regression tasks.

• Random forests are an ensemble method that combines multiple decision trees for improved accuracy.

• Neural networks are used for complex pattern recognition and pred