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I have 3 years of experience as a Business Intelligence Analyst.
Worked with a team to develop and implement data-driven strategies
Analyzed large datasets to identify trends and patterns
Created reports and dashboards to visualize data and present insights
Collaborated with stakeholders to understand business requirements
Used SQL, Excel, and Tableau for data analysis and visualization
Improved data quality and accuracy thr...
I applied via Referral and was interviewed before Jun 2023. There were 2 interview rounds.
Joins in SQL are used to combine rows from two or more tables based on a related column between them.
Joins are used to retrieve data from multiple tables based on a related column between them
Types of joins include INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN
INNER JOIN returns rows when there is at least one match in both tables
LEFT JOIN returns all rows from the left table and the matched rows from the right table
...
Normalisation is the process of organizing data in a database to reduce redundancy and improve data integrity.
Normalisation involves breaking down data into smaller, more manageable tables
It helps in reducing data redundancy by storing data in a structured way
It improves data integrity by ensuring that each piece of data is stored in only one place
Normalization is usually done in multiple stages (1NF, 2NF, 3NF, etc.) t...
Questions mostly revolved around pandas and numpy.
I applied via Campus Placement and was interviewed in Nov 2024. There were 3 interview rounds.
Apptitude and technical mcqs
I applied via Referral and was interviewed before May 2020. There was 1 interview round.
To understand the supply of restaurants in a particular area of a city, we can use various methods.
Collect data from online directories like Yelp, Zomato, etc.
Conduct surveys to gather information about the number of restaurants in the area.
Analyze the population density and demographics of the area to estimate the demand for restaurants.
Check the number of restaurant permits issued by the local government.
Use GIS mapp...
I am a data analyst with a strong background in statistics and data visualization.
Graduated with a degree in Statistics
Proficient in programming languages like Python and R
Experience in analyzing large datasets and creating data visualizations
Strong problem-solving skills and attention to detail
I have 3 years of experience as a Data Analyst in the retail industry.
Utilized SQL to extract and analyze data from databases
Created visualizations using Tableau to present insights to stakeholders
Performed statistical analysis to identify trends and patterns in sales data
I applied via Recruitment Consulltant and was interviewed before Sep 2023. There was 1 interview round.
I have over 5 years of experience in data analysis, including working with large datasets, creating visualizations, and providing actionable insights.
Experience in cleaning and transforming data to ensure accuracy and consistency
Proficient in using statistical tools and techniques to analyze data
Ability to create data visualizations and dashboards to communicate findings
Experience in identifying trends and patterns in ...
Courses in data analyst cover topics such as statistics, data visualization, machine learning, and data mining.
Statistics: Understanding of statistical concepts and techniques for data analysis.
Data Visualization: Creating visual representations of data to aid in analysis and decision-making.
Machine Learning: Using algorithms and models to analyze and make predictions based on data.
Data Mining: Extracting patterns and ...
I applied via Campus Placement and was interviewed before Apr 2022. There were 3 interview rounds.
I applied via Recruitment Consulltant and was interviewed in Jan 2024. There was 1 interview round.
I am a data analyst with a strong background in statistics and data visualization.
Graduated with a degree in Statistics
Proficient in programming languages like Python and R
Experience in analyzing large datasets and creating data visualizations
Strong problem-solving skills
Data cleaning involves removing or correcting errors in a dataset to ensure accuracy and consistency.
Remove duplicate entries
Fill in missing values
Correct formatting errors
Identify and remove outliers
Standardize data types
posted on 25 Oct 2023
Normal CAT level questions
I applied via Naukri.com and was interviewed before Dec 2022. There were 4 interview rounds.
based on 1 interview
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