Financial Software & Systems Data Analyst Interview Questions and Answers

Q1. What is difference between rank and dense rank?
Ans. 
Rank assigns unique ranks to each distinct value, while dense rank does not leave gaps between ranks.
• Rank assigns consecutive integers to each distinct value based on their order.

• Dense rank also assigns consecutive integers, but does not leave gaps between ranks.

• For example, if we have values 10, 20, 20, 30, then rank would be 1, 2, 2, 4 and dense rank would be 1, 2, 2, 3.
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Q2. What is RLS in Power Bi?
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Q1. How would you identify time for any project?
Ans. 
Identifying time for a project involves creating a timeline, setting deadlines, and monitoring progress.
• Create a project timeline outlining key milestones and tasks

• Set deadlines for each task to ensure timely completion

• Monitor progress regularly to identify any delays and adjust timelines accordingly
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Basic aptitude, basic reasoning English ah and coding mcq's.

Q1. Questions focused on SQL and powerbi.
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Easy

Q1. Reg previous project and some puzzles
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Q1. Share details of your previous job.
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Q2. Why are you looking for a change?
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It was a genuine test with quite some logical questions of math ,english,ds and some aptitude based which i clearly dont remember thoroughly but crux is mentioned

Q1. It was an one on one technical round with hiring personnel of axtria and can be termed easy to intermediate question
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Q1. This was a genuine HR or can say mangerial round where questions usually asked were asked
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Q1. What are the differences between Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN)?
Ans. 
RNNs process sequential data, while CNNs excel in spatial data analysis, like images.
• RNNs are designed for sequential data, such as time series or text.

• CNNs are optimized for grid-like data, particularly images.

• RNNs use loops to maintain memory of previous inputs, making them suitable for tasks like language modeling.

• CNNs utilize convolutional layers to detect patterns and features in images, useful in image classifica...read more
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Q2. What is a neural network, how does it function, and what strategies can be employed to avoid overfitting in a neural network?
Ans. 
A neural network is a computational model inspired by the human brain, used for pattern recognition and data analysis.
• Neural networks consist of layers of interconnected nodes (neurons) that process input data.

• They function by adjusting weights through a process called backpropagation to minimize error.

• Common strategies to avoid overfitting include using dropout layers, which randomly deactivate neurons during training...read more
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Q3. How would you approach classification problems when dealing with skewed datasets?
Ans. 
Addressing skewed datasets in classification requires techniques like resampling, using appropriate metrics, and algorithm adjustments.
• Use resampling techniques: Oversample the minority class (e.g., SMOTE) or undersample the majority class.

• Implement cost-sensitive learning: Assign higher misclassification costs to the minority class to guide the model.

• Choose appropriate evaluation metrics: Use F1-score, precision-recal...read more
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Q1. About Project Experience, most -Critical task and situation I handled , My accomplishment in current project
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Q1. Reason for job change, about axtria
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