Tokopedia Data Analyst Interview Questions and Answers

Q1. All about the past projects. Few basic data visualization concepts like what charts to use, what will be the best fit for a particular scenerio
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The assessment consists of a dataset for which we are required to build a machine learning model and submit the results along with code and detailed documentation

Q1. What are ensemble models
Ans. 
Ensemble models are machine learning models that combine multiple individual models to improve predictive performance.
• Ensemble models work by aggregating predictions from multiple models to make a final prediction.

• Common types of ensemble models include Random Forest, Gradient Boosting, and AdaBoost.

• Ensemble models are often more accurate and robust than individual models.

• They can reduce overfitting and increase genera...read more
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Q2. Difference between bagging and boosting
Ans. 
Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.
• Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.

• Boosting involves training multiple models sequentially, where each subsequent model c...read more
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Q3. A lot of tree based questions
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SQL, Python, like case about window function

Q1. All about past project
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Q1. What experience do you have using SQL?
Ans. 
I have extensive experience using SQL for data analysis and reporting.
• Proficient in writing complex SQL queries

• Experience in data manipulation, aggregation, and filtering

• Familiarity with joins, subqueries, and stored procedures

• Experience in optimizing queries for performance

• Examples: Used SQL to analyze customer behavior and create reports for marketing team, extracted data from multiple tables using joins and subqueri
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45 mins: AWS,Data warehouse,Python

Q1. Explain OOPS concepts
Ans. 
OOPS concepts refer to Object-Oriented Programming principles like Inheritance, Encapsulation, Polymorphism, and Abstraction.
• Inheritance: Allows a class to inherit properties and behavior from another class.

• Encapsulation: Bundling data and methods that operate on the data into a single unit.

• Polymorphism: Ability to present the same interface for different data types.

• Abstraction: Hiding the complex implementation detail
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Q2. Explain BigQuery
Ans. 
BigQuery is a fully managed, serverless data warehouse by Google Cloud for analyzing large datasets using SQL.
• Fully managed and serverless data warehouse

• Allows for analyzing large datasets using SQL

• Integrates with other Google Cloud services like Data Studio and AI Platform
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1.Basic SQL
2. Python based question
3.Data modelling
4. Spark
5. Cloud based questions

Sql,Python,Data Modeling and Project based questions

Q1. Salary discussion and cultural fit.
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Q2. Basic cultural fit.
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Q1. Understanding about Redshift, SQL, Data Analysis, Data Modelling
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Q2. Explain the types of Data Modelling and its concepts.
Ans. 
Data Modelling involves creating a visual representation of data to understand relationships and patterns.
• Types of Data Modelling include Conceptual, Logical, and Physical models

• Conceptual model focuses on high-level business concepts and relationships

• Logical model translates the conceptual model into a more detailed structure

• Physical model represents how the data will be stored in a database system

• Data Modelling conce...read more
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