Anko Associate Data Engineer Interview Questions and Answers

Q1. Difference between where and having
Ans. 
WHERE is used to filter rows before grouping, HAVING is used to filter groups after grouping.
• WHERE is used with SELECT statement to filter rows based on a condition

• HAVING is used with GROUP BY statement to filter groups based on a condition

• WHERE is applied before grouping, HAVING is applied after grouping

• Example: SELECT * FROM table WHERE column = 'value'

• Example: SELECT column, COUNT(*) FROM table GROUP BY column HAVIN
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Q2. View and materialised view
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Retail data case study

Case study discussion

Q1. Retail situational based questions
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Q2. Metrics used in retail business
Ans. 
Metrics used in retail business include sales, customer acquisition cost, customer lifetime value, inventory turnover, and gross margin.
• Sales: Total revenue generated from products or services sold

• Customer acquisition cost: Cost incurred to acquire a new customer

• Customer lifetime value: Predicted revenue a customer will generate over their lifetime

• Inventory turnover: Number of times inventory is sold and replaced in a ...read more
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Q1. Basic technical knowledge
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Q2. Situational and managerial round questions
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Q1. Basic salary negotiation
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Q2. Situational base question
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Sql and python questions were asked

Q1. Why are you fit for the role?
Ans. 
I am fit for the role due to my extensive experience in data analysis, strong analytical skills, and ability to communicate insights effectively.
• Extensive experience in data analysis

• Strong analytical skills

• Ability to communicate insights effectively
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Q2. Explain a project where you used data analytics to solve a business problem
Ans. 
Implemented predictive analytics model to optimize inventory management for a retail company
• Identified key factors affecting inventory levels such as seasonality, promotions, and supplier lead times

• Utilized historical sales data to forecast demand and optimize inventory levels

• Developed a predictive analytics model using machine learning algorithms to predict future sales and recommend optimal inventory levels

• Implemente...read more
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Q1. What is your expected compensation?
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Q2. When can you relocate?
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Q1. How many experience in working?
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Q2. What is your qualification?
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Q3. Where did you work earlier?
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Q4. Why did you leave work in the first place?
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Q5. Why do you need a job?
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Q1. About pyspark questions
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Q2. About etl tools
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A/B Testing, data structures

Data entry, system operator,sales management, coding sarvese

Sales management
coding sarvese
data entry
System operator working

Q1. Which was the data entry meening
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Q2. System operator
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Sales management
Coding sarvese
Operator working sales management
Group discussion

Round duration - 20 minutes
Round difficulty - Easy

Received a sudden call from one of the interviewers (Came to know this later as first round interview was with the same person). No background disturbances, but they took me by surprise.

Round duration - 90 minutes
Round difficulty - Easy

Evening time
Virtual interview from home, so choose a calm place
Interviewer really helpful and was giving ample time to solve

Round duration - 90 minutes
Round difficulty - Easy

Afternoon

Round duration - 60 minutes
Round difficulty - Easy

Evening

Q1. 
Find the Third Greatest Element
Given an array 'ARR' of 'N' distinct integers, determine the third largest element in the array.
Input:
The first line contains a single integer 'T' representing the numb...read more
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Round duration - 90 Minutes
Round difficulty - Easy

Evening.
This round is with the co-founder as he acts as the hiring manager as well. 
This round is the most tricky one and you really need to be very careful in what you answer in this interview.

Q1. Basic experience related questions
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Q1. Similar to L1.Interviewed with senior manager.
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Q1. Team fit round with Director
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Q1. Salary Discussion
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