Impact Analytics Interview Questions, Process, and Tips

Q1. Majority sql questions like Distinct total male female in department Joins Total sum of salary according to Department What is rank, Dense rank, Row number etc
Add your answer
Q2. Can you write same sql queries in python?
Ans. 
Yes, SQL queries can be written in Python using libraries like SQLAlchemy or Pandas.
• Python provides libraries like SQLAlchemy and Pandas for executing SQL queries.

• SQLAlchemy allows writing SQL queries in Python syntax and provides an Object-Relational Mapping (ORM) layer.

• Pandas provides a SQL-like interface called 'pandasql' to query DataFrames using SQL syntax.

• Both libraries offer flexibility and convenience in execut
Answered by AI
Add your answer

Q1. Full Previous company work. Explain your project And some follow up questions of outliers (if you used IQR how you treat outliers).
Add your answer
Q2. Camel puzzle question- A camel need to go from point A to B total 1k Km and Total bananas he has 3K and he will eat one banana per every km. maximum banana he can carry is 1k . Tell me how many banana he w...read more
Add your answer
Q3. One question to find that in how many days a customer is doing frequent transaction. Hint given to me is i have to use window function.
Add your answer

Q1. 2 Technical rounds were great and the panel was very welcoming.
Add your answer
Q2. Modelling and Python sql
Add your answer

Q1. Python and resume
Add your answer

Q1. Bakwas round. they took a month to schedule. didn't attend at their mentioned time 4 times. HR are worst including the Manager who interviewed. No respect for the candidates in hr round. They'll call to o...read more
Add your answer
Q2. Resume. and you can't ask challenging questions at the end. Cuz they'll disqualify you
Add your answer

React and Java Script concepts

Q1. Questions from react advanced concepts
Add your answer

Q1. HR related questions
Add your answer

Q1. What are different types of regression analysis ?
Ans. 
Different types of regression analysis include linear regression, logistic regression, polynomial regression, ridge regression, and lasso regression.
• Linear regression: Predicts a continuous outcome based on one or more input features.

• Logistic regression: Predicts the probability of a binary outcome.

• Polynomial regression: Fits a curve to the data by including polynomial terms.

• Ridge regression: Adds a penalty term to the...read more
Answered by AI
Add your answer
Q2. What is confusion matrix?
Ans. 
Confusion matrix is a table used to evaluate the performance of a classification model.
• It is a matrix with rows representing the actual class and columns representing the predicted class.

• It helps in visualizing the performance of a classification model by showing the counts of true positive, true negative, false positive, and false negative predictions.

• It is commonly used in machine learning to assess the quality of th...read more
Answered by AI
Add your answer
Q3. Questions around python programming
Add your answer

Q1. Explain the architecture of Transformer based models.
Ans. 
Transformer based models use self-attention mechanism to capture long-range dependencies in data.
• Transformer models consist of encoder and decoder layers.

• Self-attention mechanism allows each word to attend to all other words in the input sequence.

• Positional encoding is added to input embeddings to provide information about the position of words.

• Transformer models have achieved state-of-the-art results in various NLP ta...read more
Answered by AI
Add your answer
Q2. Different NLP techniques around extraction of text.
Ans. 
Various NLP techniques for text extraction include Named Entity Recognition, Part-of-Speech tagging, and Dependency Parsing.
• Named Entity Recognition (NER) identifies entities such as names, dates, and locations in text.

• Part-of-Speech tagging assigns grammatical categories to words in a sentence.

• Dependency Parsing analyzes the grammatical structure of a sentence to identify relationships between words.
Answered by AI
Add your answer