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I applied via Recruitment Consulltant and was interviewed before Nov 2023. There was 1 interview round.
In Power BI, data transformation involves cleaning, shaping, and modeling data to create visualizations.
Import data from various sources such as Excel, SQL databases, or online services
Clean and transform data using Power Query Editor
Create relationships between different data tables
Use DAX formulas to calculate new columns or measures
Design visualizations like charts, graphs, and tables to present insights
I use a variety of visualizations such as bar charts, line graphs, scatter plots, and heat maps depending on the type of data and context.
Bar charts are useful for comparing categories of data
Line graphs are great for showing trends over time
Scatter plots help in identifying relationships between variables
Heat maps are effective for visualizing large datasets and identifying patterns
I applied via Recruitment Consulltant and was interviewed before Nov 2023. There were 2 interview rounds.
Developed a predictive model for customer churn in a telecom company
Collected and cleaned customer data from various sources
Performed exploratory data analysis to identify patterns and trends
Built a machine learning model using logistic regression to predict customer churn
Evaluated the model's performance using metrics such as accuracy, precision, and recall
Various cloud technologies like AWS, Azure, and Google Cloud are commonly used for data analysis.
AWS (Amazon Web Services)
Azure (Microsoft Azure)
Google Cloud Platform
Performance based questions
Top trending discussions
I was interviewed in Aug 2017.
I was interviewed in Sep 2016.
I applied via Recruitment Consulltant and was interviewed before Jul 2021. There was 1 interview round.
I worked on a data visualization tool for tracking sales performance.
The tool was built using Tableau and SQL.
It allowed users to view sales data by region, product, and time period.
Users could also create custom dashboards and reports.
The tool helped identify trends and opportunities for improvement.
I collaborated with the sales team to ensure the tool met their needs.
I applied via Naukri.com and was interviewed in Jun 2020. There were 3 interview rounds.
I was interviewed before Nov 2016.
I was interviewed before Dec 2020.
Round duration - 120 Minutes
Round difficulty - Medium
Ninja, a new member of the FBI, has acquired some 'SECRET_INFORMATION' that he needs to share with his team. To ensure security against hackers, Ninja dec...
The task is to encode and decode 'SECRET_INFORMATION' for security purposes and determine if the transmission was successful.
Read the number of test cases 'T'
For each test case, encode the 'SECRET_INFORMATION' and then decode it
Compare the decoded string with the original 'SECRET_INFORMATION'
Print 'Transmission successful' if they match, else print 'Transmission failed'
Round duration - 60 Minutes
Round difficulty - Medium
Given an array Arr
consisting of N integers, your task is to find the equilibrium index of the array.
An index is considered as an equilibrium index if the sum of elem...
Find the equilibrium index of an array where sum of elements on left equals sum on right.
Iterate through the array and calculate prefix sum and suffix sum at each index.
Compare prefix sum and suffix sum to find equilibrium index.
Return the left-most equilibrium index or -1 if none found.
Round duration - 50 Minutes
Round difficulty - Easy
Tip 1 : Focus more on SQL
Tip 2 : Keep up with ongoing projects in the company
Tip 1 : Be honest about what you add.
Tip 2 : Don't forget to mention extra curriculars.
I applied via Recruitment Consultant and was interviewed in Aug 2020. There were 4 interview rounds.
I applied via Walk-in and was interviewed before Aug 2021. There were 2 interview rounds.
Transposing a data set involves flipping rows and columns.
Identify the data set to be transposed
Create a new table with the columns and rows flipped
Copy the data from the original table to the new table
Transpose can be done using Excel, Python, R, SQL, etc.
Example: Transposing a table of sales data to have products as rows and months as columns
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