MagicPin Senior Bdm Manager Interview Questions and Answers for Freshers

Q1. Questions related to SCM
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Q2. Bucket level creation
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Q1. Reports and tracking required.
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Q2. How to deal with low fill rate
Ans. 
Low fill rate can be dealt with by analyzing the root cause and implementing corrective actions.
• Analyze the reasons for low fill rate such as inaccurate forecasting, poor inventory management, or supplier issues

• Implement corrective actions such as improving forecasting accuracy, optimizing inventory levels, or finding alternative suppliers

• Regularly monitor and measure fill rate to ensure improvements are sustained

• Colla...read more
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Q1. Last organisation experiance
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Q1. Tell me about yourself.
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Competitive and GTM Strategy

Q1. About your previous work experience Major Achievements Strategies to solve the current problems how to enhance the productivity How to achieve the defined metrics
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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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Q1. Sql questions mostly about windows function, aggregate, using having clause in group, union vs union all, mostly basics about sql.
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Q2. Power Bi questions - measures in powerbi, calculate, dashboard, excel vs powerbi.
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Q3. Assesment 5 question based on sql and excel. Easy questions like second highest salary, manager salary, count a's.
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