Tiger Analytics Interview Questions, Process, and Tips

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Q1. Question about projects
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Q2. Why use MSE metric
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MSE metric is commonly used in data analysis to measure the average squared difference between predicted values and actual values.
• MSE helps to quantify the accuracy of a model by penalizing large errors more than small errors.

• It is easy to interpret as it gives a clear measure of how well the model is performing.

• MSE is differentiable, making it suitable for optimization algorithms like gradient descent.

• Example: In line...read more
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Q1. Discussion about projects
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Q2. Why use MSE metrics
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MSE metrics are commonly used to measure the average squared difference between predicted values and actual values in statistical analysis.
• MSE helps in evaluating the performance of a predictive model by quantifying the accuracy of the model's predictions.

• It penalizes large errors more heavily than small errors, making it a useful metric for identifying outliers or areas where the model is underperforming.

• MSE is widely...read more
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Screening round,2 programming and 5 MCQs

Q1. Basic python coding questions
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Q1. Based on CV , previous projects
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Q1. General HR discussion
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Q1. Star pattern program
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Q2. Number of vowels String program
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Count the number of vowels in a given array of strings.
• Iterate through each string in the array

• For each string, iterate through each character and check if it is a vowel (a, e, i, o, u)

• Increment a counter for each vowel found in the string
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Q1. What is top down approach
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Top down approach is a problem solving or design strategy that starts with the larger overview and breaks it down into smaller components.
• Start with a broad overview of the problem or design

• Break it down into smaller components or sub-problems

• Address each component individually before integrating them back together

• Commonly used in software development, project management, and system design
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Q2. Star vs snowflake schema
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Star schema is a denormalized schema with a single central fact table surrounded by dimension tables. Snowflake schema is a normalized schema with multiple interconnected dimension tables.
• Star schema is easier to understand and query due to denormalization.

• Snowflake schema saves storage space by normalizing data.

• Star schema is better for data warehousing and reporting, while snowflake schema is better for OLAP systems.

• ...read more
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Q1. SQL queries were given
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Q2. Design a data model
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Design a data model for a customer relationship management system
• Identify entities such as customers, products, orders, and sales representatives

• Establish relationships between entities (e.g. a customer can place multiple orders)

• Define attributes for each entity (e.g. customer name, product price)

• Consider normalization to reduce redundancy and improve data integrity
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