Kotak Mahindra Bank Assistant Manager Interview Questions, Process, and Tips

Left join is a type of SQL join that returns all the records from the left table and matching records from the right table.

• Left join is used to combine rows from two or more tables based on a related column between them.

• The result set of a left join includes all the rows from the left table and matching rows from the right table.

• If there is no match in the right table, the result set will contain NULL values for the ri...read more

SAS is a software suite used for advanced analytics, business intelligence, data management, and predictive analytics.

• SAS stands for Statistical Analysis System

• It is widely used in industries such as finance, healthcare, and retail

• SAS can perform data analysis, data mining, and predictive modeling

• It has a programming language called SAS programming language

• SAS can handle large amounts of data and is known for its relia

SAS is preferred for its reliability, security, and scalability.

• SAS has been in the market for over 40 years and has a proven track record of reliability.

• SAS provides advanced security features to protect sensitive data.

• SAS is highly scalable and can handle large amounts of data.

• SAS offers a wide range of statistical analysis and data visualization tools.

• SAS has a large community of users and provides excellent custome...read more

nodup removes duplicate observations based on all variables, nodupkey removes duplicates based on key variables only.

• nodup removes all observations that have identical values for all variables.

• nodupkey removes observations that have identical values for key variables only.

• nodupkey requires sorting the data by key variables first.

• Example: nodupkey data=dataset key=var1 var2;

• Example: nodup data=dataset;

Logistic regression assumptions include linearity, independence, and absence of multicollinearity.

• Dependent variable is binary or ordinal

• Independent variables are linearly related to the log odds of the dependent variable

• No multicollinearity among independent variables

• Observations are independent

• Large sample size

• No outliers or influential observations