Walmart Data Analyst Interview Questions and Answers

Q1. Average totals for last 3 months
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Q2. Running totals in a year using dax
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SQL questions
Window functions
Joins
Self joins

Q1. P value explanation
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P value is a statistical measure that helps determine the significance of results in hypothesis testing.
• P value is the probability of obtaining results as extreme as the observed results, assuming the null hypothesis is true.

• A small P value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, leading to its rejection.

• A large P value (> 0.05) suggests weak evidence against the null hypothesis, leadi...read more
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Q2. Statistical modeling questions
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Q1. Salary discussion
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Q1. Prepare from the job description
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Q1. Limitations of Vlookup
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Vlookup limitations include limited search range, case sensitivity, and inability to handle multiple matches.
• Vlookup only searches for values in the leftmost column of the table array

• It is case sensitive and cannot handle spelling errors

• It only returns the first match and cannot handle multiple matches

• It cannot search for values to the left of the lookup column

• It can be slow and inefficient for large datasets
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Q2. Vlookup vs Index-Match
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Vlookup and Index-Match are both Excel functions used for lookup and retrieval of data.
• Vlookup is simpler and faster but has limitations in terms of flexibility and handling of large datasets.

• Index-Match is more versatile and can handle complex data structures but is slower and requires more effort to set up.

• Vlookup is best suited for simple lookups with small datasets while Index-Match is better for more complex looku...read more
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Q3. Define Excel Functions Sum , Sum if , Count , CountA , Count Blanks
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Excel functions are pre-built formulas that perform calculations or manipulate data in a spreadsheet.
• Sum: adds up a range of numbers

• Sum if: adds up a range of numbers based on a specified condition

• Count: counts the number of cells in a range that contain numbers

• CountA: counts the number of cells in a range that are not empty

• Count Blanks: counts the number of empty cells in a range
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Q4. Limitations of Structural Query Language
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SQL limitations include lack of scalability, security vulnerabilities, and difficulty in handling unstructured data.
• SQL is not suitable for handling unstructured data like images, videos, and audio files.

• It can be difficult to scale SQL databases to handle large amounts of data.

• SQL databases can be vulnerable to security threats like SQL injection attacks.

• SQL is not always the best choice for real-time data processing ...read more
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Q5. Write code to find duplicate Records.
Ans. 
Code to find duplicate records
• Identify the key columns to check for duplicates

• Use GROUP BY and HAVING clauses to filter out duplicates

• Consider using window functions like ROW_NUMBER() to identify and remove duplicates

• Use programming languages like SQL, Python, or R to write the code
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Q6. Write code to describe database and Columns from a particular table
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Code to describe database and columns from a table
• Use SQL SELECT statement to retrieve column names and data types

• Use DESC command to get table structure

• Use INFORMATION_SCHEMA.COLUMNS to get detailed information about columns

• Use SHOW CREATE TABLE to get table creation statement
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Q7. What is trigger in SQL?
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Q8. What is the use if store procedure ?
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Stored procedures are precompiled SQL statements that can be reused and executed multiple times.
• Stored procedures improve performance by reducing network traffic and improving security.

• They can be used to encapsulate business logic and provide a consistent interface to the database.

• Stored procedures can also be used to simplify complex queries and transactions.

• Examples include procedures for inserting, updating, and de...read more
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Q1. How you get your data in your organization
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Q2. What type of challenges you face in your day today work
Ans. 
As a data analyst, I face challenges such as data quality issues, incomplete or inconsistent data, and time constraints.
• Data quality issues: Dealing with missing or inaccurate data that can affect the analysis.

• Incomplete or inconsistent data: Working with datasets that are not complete or have inconsistencies, requiring data cleaning and manipulation.

• Time constraints: Balancing multiple projects and deadlines, often ne...read more
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Q3. Sequence of Execution of SQL codes. Select - Where-from-Having- order by etc
Ans. 
The sequence of execution of SQL codes is Select-From-Where-Group By-Having-Order By.
• Select: choose the columns to display

• From: specify the table(s) to retrieve data from

• Where: filter the data based on conditions

• Group By: group the data based on a column

• Having: filter the grouped data based on conditions

• Order By: sort the data based on a column
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Q4. Difference between having and where clause
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Q5. Difference between CSV file and Excel file
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CSV files are plain text files that store tabular data, while Excel files are binary files that can contain multiple sheets and complex formatting.
• CSV files are simpler and more lightweight compared to Excel files.

• CSV files can be easily opened and edited using a text editor, while Excel files require specific software like Microsoft Excel.

• CSV files do not support formulas, macros, or formatting options like colors and...read more
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Q6. How much amount of data you Handel till now.
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I have handled large amounts of data in my previous roles.
• I have experience handling terabytes of data in my previous role as a data analyst at XYZ company.

• I have worked with data from various sources such as databases, spreadsheets, and APIs.

• I have also used tools like SQL, Python, and Excel to manipulate and analyze data.

• I am comfortable working with both structured and unstructured data.

• I have experience cleaning an...read more
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Q7. What are the different approach you use for data cleaning.
Ans. 
Different approaches for data cleaning include removing duplicates, handling missing values, correcting inconsistent data, and standardizing formats.
• Remove duplicates

• Handle missing values

• Correct inconsistent data

• Standardize formats

• Use statistical methods to identify outliers

• Check for data accuracy and completeness

• Normalize data

• Transform data types

• Apply data validation rules
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