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10+ Tredence Analyst Interview Questions and Answers

Updated 4 Oct 2024

Q1. Puzzle: Given two hour glass, one measuring 4 mins and the other 7 mins, how to measure 9 mins

Ans.

To measure 9 minutes using two hourglasses of 4 and 7 minutes, start both hourglasses simultaneously. When the 4-minute hourglass runs out, flip it again. When the 7-minute hourglass runs out, flip it again. When the 4-minute hourglass runs out for the third time, 9 minutes will have passed.

  • Start both hourglasses simultaneously

  • When the 4-minute hourglass runs out, flip it again

  • When the 7-minute hourglass runs out, flip it again

  • When the 4-minute hourglass runs out for the thir...read more

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Q2. What is your guesstimate on how many people use mobile phones in India?
Ans.

It is estimated that over 800 million people use mobile phones in India.

  • India has a population of over 1.3 billion people.

  • The mobile phone penetration rate in India is around 80%.

  • Majority of the population use mobile phones for communication, internet access, and entertainment.

  • The number of mobile phone users in India is constantly increasing due to affordable smartphones and data plans.

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Q3. How do you change the data type and push the data into a database?
Ans.

To change data type and push data into a database, use data conversion functions and SQL queries.

  • Use data conversion functions like CAST or CONVERT to change data type before pushing into the database.

  • Write SQL INSERT or UPDATE queries to push the data into the database.

  • Ensure the data being pushed matches the data type of the database column to avoid errors.

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Q4. How you reduce error in model Which kind of matrix used in your model How you map data

Ans.

To reduce error in a model, I use techniques like cross-validation, regularization, and feature selection. I use matrices like confusion matrix and correlation matrix. Data is mapped using techniques like normalization and encoding.

  • Reduce error in model by using techniques like cross-validation, regularization, and feature selection

  • Use matrices like confusion matrix to evaluate classification models and correlation matrix to analyze relationships between variables

  • Map data usi...read more

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Q5. 1.) Case Study: How Many people will drink tea on a certain day?

Ans.

The number of people who will drink tea on a certain day can vary based on factors like weather, cultural preferences, and individual habits.

  • Consider factors like weather - more people may drink tea on a cold day.

  • Take into account cultural preferences - some cultures have a strong tea-drinking tradition.

  • Individual habits play a role - regular tea drinkers are more likely to consume tea daily.

  • Survey data or sales figures can provide insights into tea consumption patterns.

  • Event...read more

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Q6. What are different optimisation techniques you have used so far in databricks

Ans.

I have used techniques like hyperparameter tuning, feature engineering, and model selection in Databricks for optimization.

  • Hyperparameter tuning using GridSearchCV or RandomizedSearchCV

  • Feature engineering to create new features or transform existing ones

  • Model selection using techniques like cross-validation or ensemble methods

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Q7. Applications of data science in other industries. 1 guestimate and puzzel

Ans.

Data science is used in various industries like finance, marketing, healthcare, and transportation to analyze trends, make predictions, and optimize processes.

  • Finance: Predictive analytics for stock market trends and risk assessment.

  • Marketing: Customer segmentation and targeted advertising campaigns.

  • Healthcare: Predictive modeling for disease diagnosis and treatment.

  • Transportation: Route optimization and demand forecasting for ride-sharing services.

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Q8. Describe any over Forecasting Methodology

Ans.

Over Forecasting Methodology involves predicting higher values than the actual outcome.

  • Over forecasting can lead to excess inventory and increased costs.

  • It can also result in missed sales opportunities due to inaccurate predictions.

  • Common causes of over forecasting include relying on outdated data or not considering external factors.

  • For example, a company may over forecast demand for a product leading to excess stock that needs to be discounted or disposed of.

  • Implementing reg...read more

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Q9. Brief overview of implementations in Salesforce

Ans.

Salesforce is a CRM platform used for various implementations like sales, marketing, customer service, etc.

  • Sales Cloud for sales automation

  • Service Cloud for customer service management

  • Marketing Cloud for marketing automation

  • Community Cloud for building online communities

  • Einstein Analytics for data analysis

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Q10. Rate yourself in sql and python

Ans.

I rate myself highly in SQL and Python.

  • I have extensive experience in writing complex SQL queries and optimizing database performance.

  • I am proficient in Python and have used it for data analysis, automation, and web scraping.

  • I have worked on various projects where I utilized both SQL and Python together to extract, transform, and load data.

  • I am familiar with popular SQL databases like MySQL, PostgreSQL, and Oracle, as well as Python libraries like pandas and SQLAlchemy.

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Q11. Explaining company's expectations

Ans.

Company's expectations should be clearly communicated to employees to ensure alignment and success.

  • Clearly outline job responsibilities and performance metrics

  • Provide regular feedback and opportunities for growth

  • Encourage open communication and collaboration within teams

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Q12. Custom reports in Salesforce

Ans.

Custom reports in Salesforce allow users to create personalized reports based on specific criteria.

  • Custom reports can be created by selecting the desired fields, filters, and grouping criteria.

  • Users can also add charts, graphs, and tables to visualize the data in the report.

  • Custom reports can be scheduled to run at specific times and be shared with other users.

  • Examples of custom reports include sales performance by region, lead conversion rates, and customer satisfaction scor...read more

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Q13. Predict sofas sold in a city

Ans.

To predict sofas sold in a city, analyze historical sales data, consider population size, income levels, housing trends, and competitor activity.

  • Analyze historical sales data to identify trends and patterns

  • Consider the population size of the city as a potential market

  • Take into account income levels of residents to determine purchasing power

  • Analyze housing trends to understand demand for furniture

  • Consider competitor activity and market saturation in the city

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Interview Process at Tredence Analyst

based on 13 interviews
3 Interview rounds
Aptitude Test Round
Technical Round
HR Round
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