Sathvik Reddy

Hii connection , "Data Lemour offers a fabulous platform for practicing interview questions for SQL or data analyst roles. With its extensive array of resources and interactive features, aspiring candidates can hone their skills and prepare effectively for interviews. Thanks to Nick Singh 📕🐒's recommendation, individuals seeking to excel in the realm of data analysis can leverage Data Lemour's curated content, mock interview sessions, and real-world scenarios to build confidence and proficiency. Whether brushing up on SQL queries or delving into complex data analytics concepts, Data Lemour provides the perfect environment to sharpen one's skills and stand out in the competitive landscape of data-related professions."

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Role: Data Analyst Long Term Send me your Resume to my E- [email protected] Senior Data Analyst Requires a minimum of five (5) years of related experience. Strong proficiency in Data visualization software like PowerBI, Tableau, and Looker. Strong proficiency in Cloud Computing Platforms such as GCP, Azure, and AWS. Experience with Data Warehousing technology like Oracle Databases, SAP HANA, Google Big Query. Strong proficiency in SQL for data querying and manipulation. Strong in programming languages such as Python and R for data analysis and scripting. Understanding of data modeling concepts and experience with data modeling tools. Experience working with machine learning, statistical techniques, and algorithms. Proficiency in ETL processes, data warehousing, and database management systems. #onsite #hybrid #remote #jobs #devops #dotnet #sdet #qa #nodejs #react #fullstack #frontend #hadoop #qualityengineer #contract #job #jobopening #openings #hiring #hiringimmediately #hotlist #sales #benchsales #benchsalesrecruiter #benchsalesrecruiters #benchsale #vendorlist #vendors #vendorslist #vendor #recruitment #recruiters #c2c #c2crequirements #c2cvendors #c2chotlist #c2cjobs #c2cusajobs #c2crequirement #c2chiring #c2croles #c2crecruiters #corp2corp #updating #requirements #requirement #c2creqs #c2cvendorlist #list #post #comment #distribution #sales #email #recruitment #linkedin #recuriting #salesrecruiters #salesrecruiter #salesrecruitment #salesrecruiting #hotlist #hotlists #hotlisting #hiring #preferred #dailyrequirements #urgentrequirement #urgenthiring #opt #usc #h1b #usitrecruitment #usitrecruiters #usbenchsales #opportunity #c2c #c2crequirements #c2crecruiters #c2cjobs #c2cconsultants #c2cvendors #c2chiring #c2chotlist #c2cavailable #c2creqs #c2croles #c2cusajobs #c2cvendorlist #c2crequirement #c2cvendores #c2cvendors #c2cvendorlist #c2cvendor #w2requirements #w2 #w2only #crop2crop #c2c #c2crecruiters #c2cconsultant #c2crequirements #c2cconsultants #c2cconsultats #c2cjobs #c2cvendors #c2creqs #c2chiring #c2chotlist #c2crequirement #c2cvendorlist #c2cvendores #c2cvendor #c2cavailable #c2croles #c2cusajobs #croptocrop #contract #vendorslist #usitrecruiting #usitrecruiters #usitbenchsales #usitjobs #usitrecruiter #usitstaffing #uscitizen #uscitizenship #usajobs #greencard #gcead #GC #w2job #w2contract #w2 #w2requirement #w2only #w2jobs #w2requirements #w2contract #hexaware #linkedinposts #linkedin #linkedinfamily #linkedinpost #linkedinconnections #linkedinconnection #linkedinjobs #uscitizen #usc #greencard #GC #Hybrid #remoteworking #remoteroles #remotework #remote #remotejobs #remotejob #remoterole #remoteopportunties #remoteroles #remote #linkedinposts #linkedinfamily #linkedinconnections #linkedinpost #linkedinconnection #linkedin

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What will I be looking for, while interviewing a fresher for Data related roles be it Data Analytics, Data Science or BI Engineer? For Data Analytics roles you need to know: 1.     Intermediate SQL- You should be able to confidently use Joins,basic window functions 2.     Basic coding skills (Python/R is fine) 3.     Basic Statistics skills – CLT,Z/T test,Hypothesis tests 4.     Guesstimate questions – Looking for the approach here 5.     Basic Visualization skills- Excel,Tableau, Looker studio,Power BI For Data Science: 1.     Intermediate SQL- You should be able to confidently use Joins,basic window functions 2.     Intermediate coding skills (Python/R)-Should be able to work with tables and Data frames 3.     Intermediate Statistics skills – CLT, Z/T test, Hypothesis tests, AUC, Accuracy metrics, errors 4.     Intermediate Machine learning skills- Should know about Fundamental modelling skills/ or should know about Neural networks, LLM is just an added advantage and not mandatory 5.     Visualization skills- Python,Excel,Tableau,Looker studio,Power BI For BI Engineer: 1.     Advanced SQL- You should be able to confidently use Joins,basic window functions,CTE,Pivot,Query optimization.Recursive query is added bonus 2.     Advanced coding skills (Python/R)-Should be able to work with tables and Data frames 3.     Advanced Visualization skills- Python,Excel,Tableau,Looker studio,Power BI But one topic should be common in all the roles above. The ability to clearly explain earlier projects. Majority of the freshers are unable to clearly answer the questions on Past projects although their resumes are filled with multiple of those. I have even heard some people say that those are just projects they did as a part of getting XYZ certification from edtech firms and don’t remember at all. Often people don’t understand why they get rejected and keep on polishing their tech skills while their inability to explain a project remains the same. If you are also looking for a change but unable to understand the reason behind the rejections, feel free to reach out for a quick chat through the below link: https://lnkd.in/g9Y-bVxt I believe I can be helpful! :) #Interview #SQL #DataAnalytics #Python #Fresher #Rejection #Resumereview #DataScience #BIE #Visualization #Tableau #Growth #help

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Hii Folks 😀 !! here’s a detailed analysis report of the sales data visualized in the Power BI dashboard: ### Sales Analysis Report **1. Sales Summary by Segment** - **Home Office**: $1.16M (50.56%) - **Corporate**: $0.71M (30.74%) - **Consumer**: $0.43M (18.7%) The majority of sales come from the Home Office segment, accounting for more than half of the total sales. Corporate and Consumer segments follow, contributing significantly but less than the Home Office segment. **2. Sales Trends by Order Date** - The sales trend over time shows multiple spikes indicating periods of high sales activity. The overall trend from 2019 to 2021 shows consistent sales with noticeable peaks. **3. Key Metrics** - **Sum of Quantity**: 38K - **Sum of Discount**: 1.56K - **Sum of Sales**: $2.30M - **Sum of Profit**: $286.40K These key metrics give an overview of the performance, with total sales amounting to $2.30M and a profit of $286.40K. **4. Sales by Sub-Category** - **Phones**: The highest sales among sub-categories, indicating strong demand. - **Chairs**: Nearly as high as phones, showing significant sales. - **Storage, Tables, Binders, Machines, Accessories, Copiers, Bookcases, Appliances**: These categories follow, with sales figures gradually decreasing. Phones and chairs dominate sales in sub-categories, while appliances show the least sales. **5. Geographic Sales Distribution** - The map visualization shows sales distribution across the United States. Sales are widespread, indicating a broad market presence. **6. Sales by Region** - **East**: $725.46K (31.58%) - **South**: $678.78K (29.55%) - **Central**: $501.24K (21.82%) - **West**: $391.72K (17.05%) Sales are highest in the East region, followed closely by the South. Central and West regions contribute significantly but less compared to the East and South. ### Insights and Recommendations - **Dominance of Home Office Segment**: Focus marketing and sales strategies on the Home Office segment, which is the largest contributor to sales. - **High Sales in Phones and Chairs**: Leverage the popularity of these sub-categories by ensuring adequate stock and promoting these products. - **Geographical Focus**: Increase sales efforts in the East and South regions, which have the highest sales. Explore opportunities to boost sales in the Central and West regions. - **Sales Trends**: Analyze the reasons behind sales spikes during certain periods to replicate successful strategies and plan for future high-sales periods. ### Conclusion This sales analysis provides a comprehensive view of the performance across different segments, sub-categories, and regions. By focusing on the insights derived, strategies can be developed to enhance sales and profitability further. https://lnkd.in/gKXu-WuH

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Interview Questions For Tableau along with Answers 1. **What is Tableau and what are its key features?** - Answer: "Tableau is a powerful data visualization tool that allows users to create interactive and shareable dashboards. Its key features include drag-and-drop functionality, real-time data analytics, and seamless integration with various data sources." 2. **Can you explain the difference between a tableau worksheet and a dashboard?** - Answer: "A Tableau worksheet is a single chart or graph that visualizes specific data, while a dashboard is a collection of multiple worksheets and objects combined on a single screen for a comprehensive view of the data." 3. **How do you handle large datasets in Tableau for optimal performance?** - Answer: "To optimize performance with large datasets, I would use techniques such as data extracts to improve query performance, data blending to combine multiple datasets efficiently, and filters to limit the data being processed." 4. **Describe your experience with Tableau Server and Tableau Online.** - Answer: "I have experience with both Tableau Server and Tableau Online for sharing and collaborating on visualizations. I've used Tableau Server to publish workbooks internally within organizations and Tableau Online for cloud-based sharing with external stakeholders." 5. **How do you approach creating effective visualizations in Tableau?** - Answer: "I start by understanding the audience and the insights they need. Then, I design visualizations that are clear, concise, and interactive, using appropriate chart types and color schemes to effectively communicate the data story." 6. **Can you explain the concept of LOD (Level of Detail) expressions in Tableau?** - Answer: "LOD expressions allow us to compute values at different levels of granularity in Tableau, such as at the data source level, visualization level, or fixed to a specific dimension. They're powerful for creating custom aggregations and addressing complex analysis requirements." 7. **How do you handle missing or incomplete data in Tableau?** - Answer: "I use Tableau's data preparation features like data blending, data cleansing, and calculated fields to handle missing or incomplete data. Depending on the situation, I might also use techniques like data imputation or filtering out incomplete records." 8. **Have you used any advanced analytics features in Tableau?** - Answer: "Yes, I've utilized advanced analytics features such as predictive modeling with Tableau's built-in algorithms, clustering analysis, and forecasting to uncover insights and make data-driven decisions." 9. **Can you explain the process of creating a calculated field in Tableau?** - Answer: "Creating a calculated field in Tableau involves defining a new field based on a formula or expression using existing fields in the data. This allows for custom calculations such as aggregations, conditional logic, and string manipulations." #PowerBi #DAX

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#collected Netflix Analytics Engineer Interview Experience: CTC - 35 LPA SQL Questions: 1️⃣ SQL Question 1: Identify VIP Users for Netflix Question: To better cater to its most dedicated users, Netflix would like to identify its “VIP users” - those who are most active in terms of the number of hours of content they watch. Write a SQL query that will retrieve the top 10 users with the most watched hours in the last month. Tables: • users table: user_id (integer), sign_up_date (date), subscription_type (text) • watching_activity table: activity_id (integer), user_id (integer), date_time (timestamp), show_id (integer), hours_watched (float) 2️⃣ SQL Question 2: Analyzing Ratings For Netflix Shows Question: Given a table of user ratings for Netflix shows, calculate the average rating for each show within a given month. Assume that there is a column for user_id, show_id, rating (out of 5 stars), and date of review. Order the results by month and then by average rating (descending order). Tables: • show_reviews table: review_id (integer), user_id (integer), review_date (timestamp), show_id (integer), stars (integer) 3️⃣ SQL Question 3: What does EXCEPT / MINUS SQL commands do? Question: Explain the purpose and usage of the EXCEPT (or MINUS in some SQL dialects) SQL commands. 4️⃣ SQL Question 4: Filter Netflix Users Based on Viewing History and Subscription Status Question: You are given a database of Netflix’s user viewing history and their current subscription status. Write a SQL query to find all active customers who watched more than 10 episodes of a show called “Stranger Things” in the last 30 days. Tables: • users table: user_id (integer), active (boolean) • viewing_history table: user_id (integer), show_id (integer), episode_id (integer), watch_date (date) • shows table: show_id (integer), show_name (text) 5️⃣ SQL Question 5: What does it mean to denormalize a database? Question: Explain the concept and implications of denormalizing a database. 6️⃣ SQL Question 6: Filter and Match Customer’s Viewing Records Question: As a data analyst at Netflix, you are asked to analyze the customer’s viewing records. You confirmed that Netflix is especially interested in customers who have been continuously watching a particular genre - ‘Documentary’ over the last month. The task is to find the name and email of those customers who have viewed more than five ‘Documentary’ movies within the last month. ‘Documentary’ could be a part of a broader genre category in the genre field (for example, ‘Documentary, History’). Therefore, the matching pattern could occur anywhere within the string. Tables: • movies table: movie_id (integer), title (text), genre (text), release_year (integer) • customer table: user_id (integer), name (text), email (text), last_movie_watched (integer), date_watched (date)

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interview questions for an entry-level data analyst role in Power BI: 1. Data Import Scenario: Describe how you would import data from various sources (Excel, SQL Server, CSV) into Power BI. 2. Data Cleaning Exercise: In Power BI, how would you handle a dataset with missing values and inconsistent formats to prepare it for analysis? 3. 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? 4. Calculated Columns and Measures: Explain how you would use calculated columns and measures in Power BI to analyze year-over-year growth. 5. 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? 6. Visualizations Task: Describe your approach to visualizing sales data in Power BI to highlight trends over time across different product categories. 7. Dashboard Optimization: A Power BI dashboard is loading slowly. What steps would you take to diagnose and improve its performance? 8. Data Refresh Scheduling: How would you set up and manage automatic data refreshes for a weekly sales report in Power BI? 9. Row-Level Security: How would you implement user-level security in Power BI for a report that needs different access levels for various users? 10. Troubleshooting a DAX Calculation: If a DAX formula in Power BI is not returning the expected results, how would you go about troubleshooting it? 11. Integration with Other Tools: Describe a scenario where you integrated Power BI with another tool or service (like Excel, Azure, or a web AΡΙ). 12. Interactive Reports Creation: How would you design a Power BI report that allows user interaction, such as using slicers or drill-down features? 13. 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? 14. Sharing Reports: Explain how you would share a report with your team and set up access controls using Power BI Service. 15. SQL Queries in Power BI: How do you use SQL queries in Power BI for advanced data transformation or analysis? 16. Error Handling in Data Sources: How do you manage and resolve errors in data sources or calculations in Power BI? 17. Custom Visuals Usage: Have you used custom visuals in Power BI? Describe the scenario and the benefits. 18. Power BI Templates: Provide an example of a situation where you created or used a Power BI template. What advantages did this offer? 19. Collaboration in Power BI Projects: Discuss how you have worked with others on a Power BI project. What collaboration tools or features within Power BI did you utilize? 20. Performance Tuning: What steps do you take to ensure your Power BI reports are performing optimally when dealing with large datasets or complex calculations?

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Deloitte Data Analyst Interview Experience (0-3 Years) Skills Tested: SQL, Power BI SQL Questions (5 questions) 1. Difference between RANK(), DENSE_RANK(), and ROW_NUMBER(): - Explain the differences between these window functions with examples. 2. Find the nth highest salary: - Using the employee table (columns: EmpID, ManagerID, JoinDate, Dept, Salary), write a query to find the nth highest salary. 3. Find employees under a specific manager (including subordinates at any level): - Given an employee table with EmpID and ManagerID, write a query to retrieve all employees reporting to a specific manager, including their subordinates at any level. 4. Cumulative salary by department for employees who joined in the last 30 days: - Write a query to calculate the cumulative salary of employees in each department who have joined in the past 30 days. 5. Top 2 customers with highest order amount per product category (handling ties): - Using the customer table (columns: CustomerID, ProductCategory, OrderAmount), find the top 2 customers with the highest order amounts for each product category, ensuring ties are handled correctly. Power BI Questions (3 questions) 1. Creating a Sales Dashboard: - Walk through the step-by-step process of creating a sales dashboard from scratch in Power BI. 2. Optimizing a Slow Power BI Report: - Explain how you would optimize a Power BI report that is running slowly. 3. Chart Types and Their Uses: - Describe five different chart types in Power BI and explain their uses in representing various aspects of data. Behavioral Questions (2 questions) 1. Why Data Analyst and Why Deloitte? - Why did you choose to become a data analyst, and what motivated you to apply to Deloitte specifically? 2. Managing a Difficult Task with Tight Deadlines: - Share an example of a time when you had to handle a challenging task with a tight deadline. How did you approach and manage the situation? Follow Kunal Giri for more

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Recent Tech Round -1 (Part-2) Interview Questions asked By a MNC company for Senior Data analyst(SQL, Power BI) role having experience 4-6 years. Question 1.  How will you create a calculated column in Power BI to categorize orders as "High" if the sales amount is above average and "Low" otherwise? Question 2.  How would you calculate the Year-to-Date (YTD) sales in Power BI? Question 3.  How can you create a dynamic measure in Power BI that shows sales as a percentage of total sales for the selected category? Question 4.  What is difference between a measure and a calculated Column. Question 5.  What are the things you keep in your mind while choosing a visual in your Report/Dashboard. #dataanalyst #interview #powerbi

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#TigerAnalytics Data Analyst Interview Experience (0-3 years) SQL Questions: 1. Describe a scenario where you used SQL to analyze customer data. What insights did you uncover? 2. Rate your SQL skills on a scale of 1-10 and provide examples of advanced queries you’ve written. 3. Write a query to identify the second-highest salary in each department. 4. Explain the concept of JOINs and provide a query that joins three tables (Orders, Customers, Products) to find the top 5 customers by revenue. 5. What is a Common Table Expression (CTE) in SQL, and when would you use it? Write a CTE query to calculate cumulative monthly sales. 6. Write an SQL query to find all employees whose salaries are above the department average. 7. Describe your approach to optimizing SQL queries. Can you share an example where optimization made a noticeable difference? Python Questions: 1. What Python libraries do you frequently use for data manipulation, and why? 2. How would you write a Python function to calculate moving averages for sales data? 3. Write a Pandas code snippet to remove outliers from a dataset based on the IQR method. 4. Describe a project where you used Matplotlib or Seaborn for data visualization. What insights did your visualizations reveal? 5. How would you merge three DataFrames (Sales, Customers, Regions) and compute the average sales per region? 6. Write a Python code snippet to group data by product category and calculate total revenue for each category. 7. How do you handle missing data in Python? Share a few imputation techniques you use. 8. Explain how you would use time series analysis in Python for forecasting monthly sales. #SQL #Python #Excel #DataAnalyst #BiAnalyst #PowerBi #Jobs

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Role: Data Analyst - Data Governance Analyst Location: Jackson, Mississippi -39201 -- Hybrid Note: Only Locals Job Description Processing Data and Public Records Requests: Receiving Requests: ·        Receive and log incoming data and public records requests from non-media parties. ·        Ensure requests are properly documented and tracked for timely processing. Legal Review and Redaction: ·        Assist in legal review of requested documents to determine necessary redactions to protect sensitive information before release as public records. ·        Ensure compliance with legal requirements and agency policies regarding public records disclosures. Data Retrieval and Compilation: ·        Coordinate with relevant departments or personnel to retrieve requested data and compile necessary documents for disclosure. ·        Ensure completeness and accuracy of information provided in response to requests. Response Preparation: ·        Prepare responses to data and public records requests in accordance with established timelines and legal requirements. ·        Draft correspondence and documentation ensuring clarity and completeness in responses. delivery of requested information. ·        Maintain records of communications and actions taken related to each request. Microsoft Purview Oversight: ·        Serve as the primary compliance contact for the implementation and oversight of the agency’s Microsoft Purview application. ·        Data types to be brought under Purview oversight and management include: data/files within enterprise Microsoft 365 applications (Outlook, SharePoint, OneDrive, Teams, Exchange, etc.) and other on-premises, multicloud, and software as a service (SaaS) data. Data cover a range of public health subject matters such as: disease surveillance and reporting, environmental health (water supply, wastewater, food protection, etc.), vital records and statistics, and professional and healthcare facility licensure, just to name a few. Data Management and Systems Development: ·        Collaborate with the Director of Data Governance in developing and designing data management applications and systems. ·        Aim to improve the agency’s data capabilities for public health purposes. ·        Provide general support to the agency in its projects funded under the CDC Public Health Infrastructure Grant (PHIG), specifically, under Strategy A3: Data Modernization. Projects include: ·        Cataloging and organization of agency data resources with the ultimate goal of creating a public facing agency-wide data catalog, ·        Assisting with the selection and implementation of an updated process for managing external requests for data and public records ·        Supporting the creation and implementation of project timelines ·        Consistent and effective communication with agency staff supporting the projects, and maintaining focus on project goals and meeting deadlines Interested please share resumes to [email protected]

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McKesson Compile is hiring Software Development Intern!(Bengaluru) Requirements: •Data Pipeline Development: - Write code to build and optimize data pipelines. - Ensure data integrity and consistency across various stages of the pipeline. •Data Quality and Testing: - Implement data validation and quality checks. - Conduct testing to ensure data pipelines are robust and reliable. •Data Integration: - Assist in integrating diverse data sources, including APIs, databases, and flat files. - Help in the development of data ingestion processes. •Documentation: - Document data workflows, pipeline structures, and data models. - Create user guides and technical documentation for future reference. •Performance Tuning: - Monitor and optimize the performance of data pipelines and platforms. - Assist in troubleshooting and resolving performance issues. •Tool and Technology Utilization: - Utilize data engineering tools and technologies such as SQL, Python, Apache Spark, Hadoop, etc. - Gain hands-on experience with cloud platforms like AWS, Azure, or Google Cloud Platform. •Data Analysis and Reporting: - Support data analysis tasks and generate reports as needed. - Use data visualization tools to present insights and findings. •Compliance and Security: - Ensure compliance with data governance and security policies. - Assist in implementing data protection measures and access controls. Apply here:https://lnkd.in/dkuE-9GZ

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Round 2 - Case Study Myntra Data Analyst Interview Experience - Round 2 Hey Everyone! 👋 I’m back with Round 2 of my Myntra Data Analyst interview experience. This round was all about **Case Studies** and a bit of **Resume Grilling**. 🔹 **Case Study 1**: I was asked to **estimate the number of Uber cars** in Bengaluru. This is a classic **guess-estimate** question. I started by assuming some basic numbers like **population**, **car ownership**, and **Uber’s market share** to come up with a reasonable estimate. Remember, the key here is to explain your **thought process** clearly! 🚗 🔹 **Case Study 2**: The second question was about solving an issue with **fraudulent customer behavior** at Myntra. I was asked to **list metrics** that could help identify fraud and suggest **actionable solutions**. Metrics like **order frequency**, **shipping address patterns**, and **payment method inconsistencies** were key indicators. I also suggested using **machine learning models** to flag suspicious behavior and reduce fraud. 🔒 🔹 **Resume Grilling**: They also asked about the projects listed on my resume. They wanted to know more about the **challenges**, **tools used**, and the **impact** of my previous work. So, always be ready to explain your projects in detail! ✍️ In my next post, I’ll share the experience from the **Hiring Manager round**. ✨ stay connected with me Manjunath Kore #DataAnalyst #CaseStudy #MyntraInterview #DataScience #FraudDetection #UberCars #AnalyticsJourney #DataMetrics #manjunathkore

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𝐏𝐨𝐰𝐞𝐫 𝐁𝐢 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝐀𝐬𝐤𝐞𝐝 𝐈𝐧 #𝐓𝐞𝐜𝐡𝐌𝐚𝐡𝐢𝐧𝐝𝐫𝐚 Calling all freshers/aspiring data analysts and especially #powerbi enthusiasts ! Today, I am sharing the Power BI interview questions that were asked in a service-based company, Tech Mahindra, along with their answers. Note: Reposting For New Audiences 1. How to handle missing values? 2. Explain the difference between Calculated Column and Measure? 3. What is DAX and give an example? 4. Explain RLS (Row Level Security) and how do you implement RLS 5. How do you disable a graph that is changing dynamically? 6. Explain the process of publishing a report? 7. How to perform Join operations? 8. How to create relationships in Power BI? 9. Good Practices in Power BI? 10. How many types or roles are available in power bi service and what was your role? More Questions on Part 2 soon Hope you found this Valuable & Helpful. If any query please comment below. Follow Prem Mandal For More #powerbi #techmahindra #interview #questions

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𝐏𝐨𝐰𝐞𝐫 𝐁𝐢 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝐀𝐬𝐤𝐞𝐝 𝐈𝐧 #𝐓𝐞𝐜𝐡𝐌𝐚𝐡𝐢𝐧𝐝𝐫𝐚 Calling all freshers/aspiring data analysts and especially #powerbi enthusiasts ! Today, I am sharing the Power BI interview questions that were asked in a service-based company, Tech Mahindra, along with their answers. Note: Reposting For New Audiences 1. How to handle missing values? 2. Explain the difference between Calculated Column and Measure? 3. What is DAX and give an example? 4. Explain RLS (Row Level Security) and how do you implement RLS 5. How do you disable a graph that is changing dynamically? 6. Explain the process of publishing a report? 7. How to perform Join operations? 8. How to create relationships in Power BI? 9. Good Practices in Power BI? 10. How many types or roles are available in power bi service and what was your role? More Questions on Part 2 soon Hope you found this Valuable & Helpful. If any query please comment below. Follow Prem Mandal For More #powerbi #techmahindra #interview #questions

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#GoldmanSachs Data Analyst Interview Experience (2+ years) #SQL: 1. Calculate the average salary for each department from the table. 2. Write a SQL query to display the employee's name along with their manager's name using a self-join on the 'employees' table, which contains 'emp_id', 'name', and 'manager_id' columns. 3. Find the most recent hire for each department (solved using LEAD/LAG functions). 4. Write a query to retrieve the nth highest salary from the Employees table, which has 'EmployeelD', 'Name', and 'Salary' columns. #PowerBI: 1. What is meant by Filter context in DAX? 2. Explain the process of implementing Row-Level Security (RLS) in Power BI. 3. Describe the different types of filters available in Power BI. 4. What's the difference between the 'ALL' and 'ALLSELECTED' functions in DAX? 5. How would you use DAX to calculate total sales for a specific product?Python: 1. Create a dictionary, add elements, update a specific entry, and print the dictionary sorted by key in alphabetical order. 2. Identify unique values from a list of numbers and print how many times each value occurs. 3. Find and print the duplicate values in a list of numbers, along with their frequency. In addition to the technical questions, one of the rounds focused primarily on my previous work experience and included a case study discussions

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