Dailyhunt Senior Data Analyst Interview Questions and Answers

Q1. When I initially joined my job right after college there was a point where I was constantly
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Q2. It's a great organisation and I've learner a lot here but it's such a small company that it's difficult to find ways to move up ask yourself what makes you feel passionate or happy when you work😊
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Q3. Opportunity great time interest must
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Group discussion can also provide feedback to instructors on participant comprehension.

1. Tell me about yourself
2. Estimate the number of hospitals in India

1. There has been a decrease in 20% of the users in the past 3 days in online pharmacy application, what will you do now?

Q1. Salary negotiation on what were last salary and related questions
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Q2. How soon can you join?
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Q3. Are you holding any other offer, in case you do..they will try to match it which ideally depends on your interview.
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Q4. Are you comfortable relocating to the office location?
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Q1. Introduction of yourself
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Assignment of Google sheets

Q1. Self introduction
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Q2. What do you know about analysis and logical reasoning
Ans. 
Analysis and logical reasoning involve examining data, identifying patterns, and drawing conclusions based on evidence.
• Analysis involves breaking down complex information into smaller components for better understanding.

• Logical reasoning is the process of using rational thinking to make sense of information and draw valid conclusions.

• Analytical skills are essential for interpreting data accurately and making informed d...read more
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Q1. SQL joins, case study
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Case study guesstimates

Case study, guesstimates

Q1. Just dirty politics to negotiate and to ruin your offer
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Q1. 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 unique ranks to each distinct value in a dataset

• Dense rank does not leave gaps between ranks, assigning consecutive ranks to values with the same rank

• For example, if values are 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. How will merge multiple file in python
Ans. 
Merge multiple files in Python using pandas.concat() or pd.merge() functions.
• Use pandas.concat() function to merge multiple files vertically (row-wise).

• Use pd.merge() function to merge multiple files horizontally (column-wise) based on a common column.

• Ensure that the files have compatible column names and data types before merging.

• Handle any missing or duplicate values appropriately during the merging process.

• Consider ...read more
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Q3. Data frame explain in detail
Ans. 
A data frame is a two-dimensional data structure in which data is stored in rows and columns.
• Data frames are commonly used in programming languages like R and Python for data analysis.

• Each column in a data frame represents a variable, while each row represents an observation.

• Data frames can contain different types of data, such as numeric, character, and factor.

• Data frames can be created from various sources like CSV f
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