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Advanced Questions Asked by Big 4 📊 Excel Questions 1. How do you use Excel to forecast future trends based on historical data? Describe a scenario where you built a forecasting model. 2. Can you explain how you would automate repetitive tasks in Excel using VBA (Visual Basic for Applications)? Provide an example of a complex macro you created. 3. Describe a time when you had to merge and analyze data from multiple Excel workbooks. How did you ensure data integrity and accuracy? 🗄 SQL Questions 1. How would you design a database schema for a new e-commerce platform to efficiently handle large volumes of transactions and user data? 2. Describe a complex SQL query you wrote to solve a business problem. What was the problem, and how did your query help resolve it? 3. How do you ensure data integrity and consistency in a multi-user database environment? Explain the techniques and tools you use. 🐍 Python Questions 1. How would you use Python to automate data extraction from various APIs and combine the data for analysis? Provide an example. 2. Describe a machine learning project you worked on using Python. What was the objective, and how did you approach the data preprocessing, model selection, and evaluation? 3. Explain how you would use Python to detect and handle anomalies in a dataset. What techniques and libraries would you employ? 📈 Power BI Questions 1. How do you create interactive dashboards in Power BI that can dynamically update based on user inputs? Provide an example of a dashboard you built. 2. Describe a scenario where you used Power BI to integrate data from non-traditional sources (e.g., web scraping, APIs). How did you handle the data transformation and visualization? 3. How do you ensure the performance and scalability of Power BI reports when dealing with large datasets? Describe the techniques and best practices you follow. 💡 Tips for Success: Understand the business context: Tailor your answers to show how your technical skills solve real business problems. Provide specific examples: Highlight your past experiences with concrete examples. Stay updated: Continuously learn and adapt to new tools and methodologies. I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02 Hope it helps :)

Some practical interview questions for data analyst role in Power BI: • Data Import Scenario: Describe how you would import data from various sources (Excel,SQL Server, CSV) into Power BI. • Data Cleaning Exercise: In Power BI, how would you handle a dataset with missing values and inconsistent formats to prepare it for analysis? • Handling Large Datasets: If you're working with a very large dataset in Power BI that is causing performance issues, what strategies would you use to optimize the data processing? • Calculated Columns and Measures: Explain how you would use calculated columns and measures in Power BI to analyze year-over-year growth. • Data Modeling Case: You have sales data in one table and customer data in another. How would you create a data model in Power BI to analyze customer purchase behavior? • Visualizations Task: Describe your approach to visualizing sales data in Power BI to highlight trends over time across different product categories. • Dashboard Optimization: A Power BI dashboard is loading slowly. What steps would you take to diagnose and improve its performance? • Data Refresh Scheduling: How would you set up and manage automatic data refreshes for a weekly sales report in Power BI? • Row-Level Security: How would you implement user-level security in Power BI for a report that needs different access levels for various users? • Troubleshooting a DAX Calculation: If a DAX formula in Power BI is not returning the expected results, how would you go about troubleshooting it? • Integration with Other Tools: Describe a scenario where you integrated Power BI with another tool or service (like Excel, Azure, or a web API). • Interactive Reports Creation: How would you design a Power BI report that allows user interaction, such as using slicers or drill-down features? • Adapting to Data Source Changes: If there are structural changes in a primary data source (like addition or removal of columns), how would you update your Power BI reports and dashboards? • Sharing Reports: Explain how you would share a report with your team and set up access controls using Power BI Service. • SQL Queries in Power BI: How do you use SQL queries in Power BI for advanced data transformation or analysis? • Error Handling in Data Sources: How do you manage and resolve errors in data sources or calculations in Power BI? • Custom Visuals Usage: Have you used custom visuals in Power BI? Describe the scenario and the benefits. • Power BI Templates: Provide an example of a situation where you created or used a Power BI template. What advantages did this offer? • Performance Tuning: What steps do you take to ensure your Power BI reports are performing optimally when dealing with large datasets or complex calculations? I have curated the best interview resources to crack Power BI Interviews 👇👇 https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c Hope you'll like it Like for more 👍❤️

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How to become a "Data Analyst" in 36 weeks? Here's the plan - ☞ Microsoft Excel (First 18 Weeks) (Mon-Fri) ☞ Power BI (Next 18 Weeks) (Mon-Fri) ☞ SQL (All 36 weeks) (Sat & Sun) Important Point :- ➜ Spend 2.5 hour's ( Mon - Fri) ➜ Spend 4 hour's ( Sat & Sun) ➜ Follow the Limited resources to avoid Confusion I have curated best Data Analytics Resources 👇👇 https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02 Like if it helps :)

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𝗪𝗮𝗻𝘁 𝘁𝗼 𝗸𝗻𝗼𝘄 𝘄𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝘀 𝗶𝗻 𝗮 𝗿𝗲𝗮𝗹 𝗱𝗮𝘁𝗮 𝗮𝗻𝗮𝗹𝘆𝘀𝘁 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄? 𝗕𝗮𝘀𝗶𝗰 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 -Brief introduction about yourself. -Explanation of how you developed an interest in learning Power BI despite having a chemical background. 𝗧𝗼𝗼𝗹𝘀 𝗣𝗿𝗼𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 -Discussion about the tools you are proficient in. -Detailed explanation of a project that demonstrated your proficiency in these tools. 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗘𝘅𝗽𝗹𝗮𝗻𝗮𝘁𝗶𝗼𝗻 Explain about any Data Analytics Project you did, below are some follow-up questions for sales related data analysis project Follow-up Question: Was there any improvement in sales after building the report? Provide a clear before and after scenario in sales post-report creation. What areas did you identify where the company was losing sales, and what were your recommendations? - How do you check the quality of data when it's given to you? Explain your methods for ensuring data quality. - How do you handle null values? Describe your approach to managing null values in datasets. 𝗦𝗤𝗟 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 -Explain the order in which SQL clauses are executed. -Write a query to find the percentage of the 18-year-old population. Details: You are given two tables: Table 1: Contains states and their respective populations. Table 2: Contains three columns (state, gender, and population of 18-year-olds). -Explain window functions and how to rank values in SQL. - Difference between JOIN and UNION. -How to return unique values in SQL. 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 -Solve a puzzle involving 3 gallons of water in one jar and 2 gallons in another to get exactly 4 gallons. Step-by-step solution for the water puzzle. - What skills have you learned on your own? Discuss the skills you self-taught and their impact on your career. -Describe cases when you showcased team spirit. -⭐ 𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮 𝗔𝗽𝗽 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻 Scenario: Choose any social media app (I choose Discord). Question: What function/feature would you add to the Discord app, and how would you track its success? - Rate yourself on Excel, SQL, and Python out of 10. - What are your strengths in data analytics? I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02 Like if it helps :)

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Some Imp Scenario Q & A for product based Company : You are a data analyst at a logistics company. The company wants to analyze delivery performance and customer satisfaction. Your tasks are: 1. Identify late deliveries and their impact on customer satisfaction. 2. Calculate the average delivery time for each region. 3. Create a Power BI report to visualize delivery performance and identify areas for improvement Answer: SQL Queries to Retrieve Data 1. Identify Late Deliveries and Their Impact on Customer Satisfaction: SELECT d.DeliveryID, d.CustomerID, d.DeliveryDate, d.ExpectedDeliveryDate, d.DeliveryTime, c.SatisfactionScore FROM Deliveries d JOIN Customers c ON d.CustomerID = c.CustomerID WHERE d.DeliveryDate > d.ExpectedDeliveryDate; 2. Calculate the Average Delivery Time for Each Region: SELECT Region, AVG(DATEDIFF(day, OrderDate, DeliveryDate)) AS AvgDeliveryTime FROM Deliveries GROUP BY Region; 3. Customer Satisfaction by Delivery Performance: SELECT DeliveryPerformance, AVG(SatisfactionScore) AS AvgSatisfactionScore FROM ( SELECT d.CustomerID, c.SatisfactionScore, CASE WHEN d.DeliveryDate <= d.ExpectedDeliveryDate THEN 'On Time' ELSE 'Late' END AS DeliveryPerformance FROM Deliveries d JOIN Customers c ON d.CustomerID = c.CustomerID ) AS DeliveryData GROUP BY DeliveryPerformance; Import Data into Power BI 1. Load Data: Open Power BI Desktop. Use the "Get Data" feature to connect to your SQL database. Import the result sets from the SQL queries into Power BI. 2. Create Relationships (if necessary): Ensure that the data tables are properly related, such as linking the Deliveries table to the Customers table. Create Visualizations 1. Late Deliveries and Their Impact on Customer Satisfaction: Create a table visual. Drag DeliveryID, CustomerID, DeliveryDate, ExpectedDeliveryDate, DeliveryTime, and SatisfactionScore to the Values. 2. Average Delivery Time for Each Region: Create a bar chart. Drag Region to the Axis. Drag AvgDeliveryTime to the Values. 3. Customer Satisfaction by Delivery Performance: Create a bar chart. Drag DeliveryPerformance to the Axis. Drag AvgSatisfactionScore to the Values. 4. Overall Delivery Analysis: Create a pie chart. Drag Region to the Legend. Drag AvgDeliveryTime to the Values. Optimize Performance 1. Data Model Optimization: Filter data to include only necessary columns and rows. Use summarized tables to pre-aggregate data. 2. DAX Optimization: Create measures for dynamic calculations. Simplify DAX formulas to improve performance. 3. Visualization Optimization: Limit the number of visuals per page. Avoid excessive use of slicers or custom visuals that can impact performance. I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02 Like if it helps :)

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Amazon Data Analyst Interview Questions for 1-3 years of experience role :- A. SQL: 1. You have two tables: Employee and Department. - Employee Table Columns: Employee_id, Employee_Name, Department_id, Salary - Department Table Columns: Department_id, Department_Name, Location Write an SQL query to find the name of the employee with the highest salary in each location. 2. You have two tables: Orders and Customers. - Orders Table Columns: Order_id, Customer_id, Order_Date, Amount - Customers Table Columns: Customer_id, Customer_Name, Join_Date Write an SQL query to calculate the total order amount for each customer who joined in the current year. The output should contain Customer_Name and the total amount. B. Python: 1. Basic oral questions on NumPy (e.g., array creation, slicing, broadcasting) and Matplotlib (e.g., plot types, customization). 2. Basic oral questions on pandas (like: groupby, loc/iloc, merge & join, etc.) 2. Write the code in NumPy and Pandas to replicate the functionality of your answer to the second SQL question. C. Leadership or Situational Questions: (Based on the leadership principle of Bias for Action) - Describe a situation where you had to make a quick decision with limited information. How did you proceed, and what was the outcome? (Based on the leadership principle of Dive Deep) - Can you share an example of a project where you had to delve deeply into the data to uncover insights or solve a problem? What steps did you take, and what were the results? (Based on the leadership principle of Customer Obsession) - Tell us about a time when you went above and beyond to meet a customer's needs or expectations. How did you identify their requirements, and what actions did you take to deliver exceptional service? D. Excel: Questions on advanced functions like VLOOKUP, XLookup, SUMPRODUCT, INDIRECT, TEXT functions, SUMIFS, COUNTIFS, LOOKUPS, INDEX & MATCH, AVERAGEIFS. Plus, some basic questions on pivot tables, conditional formatting, data validation, and charts. I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://whatsapp.com/channel/0029VaGgzAk72WTmQFERKh02 Like if it helps :)