Innoviti Technologies Private Limited Data Analyst Interview Questions and Answers

Q1. Tell me brief about your self
Ans. 
I am a data analyst with a strong background in statistics and data visualization.
• Experienced in analyzing large datasets using SQL, Python, and R

• Skilled in creating insightful reports and dashboards using Tableau and Power BI

• Strong communication skills to present findings to stakeholders

• Certified in data analysis and machine learning techniques
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Q2. What are youre strenth and weekness
Ans. 
My strength lies in my analytical skills and attention to detail, while my weakness is sometimes getting too caught up in the details.
• Strength: Strong analytical skills

• Strength: Attention to detail

• Weakness: Getting caught up in details (provide example)
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Q1. Basics of Logistic regression
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Q2. What is Logistic Regression? What is Recall
Ans. 
Logistic Regression is a statistical method used to model the probability of a certain event occurring based on one or more predictor variables. Recall is a metric used to evaluate the performance of a classification model.
• Logistic Regression is used for binary classification tasks, where the outcome variable is categorical and has two classes.

• It estimates the probability that a given input belongs to a certain categor...read more
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Q3. What is Recall?
Ans. 
Recall is a metric used in classification models to measure the ability of the model to find all relevant cases within a dataset.
• Recall is calculated as the number of true positive predictions divided by the sum of true positive and false negative predictions.

• It is also known as sensitivity or true positive rate.

• A high recall indicates that the model is good at identifying all relevant cases, even if it means more fals...read more
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Q4. What is the difference between linear and logistic reg.?
Ans. 
Linear regression is used for predicting continuous values, while logistic regression is used for predicting binary outcomes.
• Linear regression is used when the target variable is continuous and has a linear relationship with the independent variables.

• Logistic regression is used when the target variable is binary or categorical and the relationship between independent variables and the target is non-linear.

• Linear regres...read more
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Q5. What are the performance metrics of Regression
Ans. 
Performance metrics of Regression include Mean Squared Error, R-squared, Mean Absolute Error, etc.
• Mean Squared Error (MSE)

• R-squared (R^2)

• Mean Absolute Error (MAE)

• Root Mean Squared Error (RMSE)

• Adjusted R-squared
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Q1. Fibonacci sequence
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Q2. Databricks cluster questions
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Q3. Intermediate SQL questions from datalemur
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Q4. Python questions from geeksforgeeks
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Q5. ETL information
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Q1. Explain the project architecture.
Ans. 
The project architecture consists of multiple components that work together to process and analyze data.
• The architecture follows a distributed computing model.

• Data is collected from various sources and stored in a data lake or data warehouse.

• Data processing and transformation tasks are performed using tools like Apache Spark or Hadoop.

• Processed data is then loaded into a database or data store for further analysis.

• Anal...read more
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Q2. What are flaws in your architecture?
Ans. 
Our architecture lacks scalability and real-time processing capabilities.
• Our current architecture is not designed to handle large volumes of data.

• Real-time processing of data is not possible with our current setup.

• We lack a proper data pipeline for efficient data processing.

• Our architecture is not fault-tolerant and lacks redundancy.

• We need to improve our data storage and retrieval mechanisms.

• Our architecture does not ...read more
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Basic technology function of MODEM and it's working via SM to master .

Doubt in honesty while e and eco of functional programming.

Technical SQL Coding Round of 1 hour

Began with 2 easy generic question -
1. No. of record on different types of joins.
2. Employees who have higher salaries than their managers,

Then moved to medium questions -
1. Implement Rolling sum with & without window functions.
2. Other questions were on CTEs, Joins & other complex queries.

Bar Raiser Round of 1 hour involving -

1. Case study: How can we leverage product knowledge & analytics to increase Amazon Prime Revenue from 10% to 12%?

2. Metrics awareness: Common metrics discussion like DAU, PDAU, MAU, Retention, Churn, etc.

3. Resume based work exp discussion

Q1. Quick culture fitment round with HR discussing about past work experience, my expectations & why I want to join Jupiter.
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Q1. Tell me brief about your self
Ans. 
I am a data analyst with a strong background in statistics and data visualization.
• Experienced in analyzing large datasets using SQL, Python, and R

• Skilled in creating insightful reports and dashboards using Tableau and Power BI

• Strong communication skills to present findings to stakeholders

• Certified in data analysis and machine learning techniques
Answered by AI
Add your answer
Q2. What are youre strenth and weekness
Ans. 
My strength lies in my analytical skills and attention to detail, while my weakness is sometimes getting too caught up in the details.
• Strength: Strong analytical skills

• Strength: Attention to detail

• Weakness: Getting caught up in details (provide example)
Answered by AI
Add your answer