Signify Senior Data Analyst Interview Questions and Answers

Easy to answer ,asked mostly on sql and other ml topics

Q1. Differencde between sql and nosql
Ans. 
SQL is a relational database management system, while NoSQL is a non-relational database management system.
• SQL databases are table-based and have a predefined schema, while NoSQL databases are document-based, key-value pairs, graph databases, or wide-column stores.

• SQL databases are good for complex queries and transactions, while NoSQL databases are better for hierarchical data storage and real-time web applications.

• Ex...read more
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Q2. What are the regularization in ml
Ans. 
Regularization in machine learning is a technique used to prevent overfitting by adding a penalty term to the model's loss function.
• Regularization helps in reducing the complexity of the model by penalizing large coefficients.

• Common types of regularization include L1 (Lasso) and L2 (Ridge) regularization.

• L1 regularization adds the absolute value of the coefficients to the loss function, promoting sparsity.

• L2 regulariza...read more
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Basic python questions

Q1. Asked to create a power bi dashboard
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Q1. Had coding test on SQL and Python
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Q1. Sql rank order explain
Ans. 
SQL rank order function explanation
• Rank order function in SQL assigns a rank to each row based on a specified column

• It can be used to determine the top or bottom N records in a dataset

• Example: SELECT column1, column2, RANK() OVER (ORDER BY column3 DESC) AS rank_order FROM table_name
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Q2. Merging two tables
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Merging two tables involves combining data from both tables based on a common key.
• Identify a common key between the two tables

• Use SQL JOIN statements to merge the tables

• Choose the appropriate type of join (e.g. inner join, outer join)

• Consider the size of the tables and the performance implications of the merge
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SQL coding and MCQ duration 45 min

Q1. Job responsibilities
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Q2. Power BI, tableau, SQL, python
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Q1. Tell me about yourself
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Q1. About yourself n work profile
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It was simple but lengthy

Q1. Tell me about yourself
Ans. 
I am a data analyst with a strong background in statistics and data visualization.
• Graduated with a degree in Statistics

• Proficient in programming languages like Python and R

• Experience in analyzing large datasets and creating data visualizations

• Strong problem-solving skills
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Q2. About resume and technical
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15 statistical and logical questions

2 easy to medium coding problmes. e.g. swapping the array.

Q1. What is regression ? how it works
Ans. 
Regression is a statistical method used to analyze the relationship between variables and predict outcomes.
• Regression models the relationship between a dependent variable and one or more independent variables.

• It works by finding the best-fit line that minimizes the sum of squared differences between the actual and predicted values.

• Examples include linear regression, polynomial regression, and logistic regression.
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Q2. Questions on recent projects
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Q1. Basic back ground check
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