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SQL Queries Code Interviews QA 50 plus

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Here are SQL-focused interview questions with only the relevant SQL code: 1. Find the second highest salary from an Employee table. SELECT MAX(Salary) AS SecondHighestSalary FROM Employees WHERE Salary < (SELECT MAX(Salary) FROM Employees); Using ROW_NUMBER(): WITH RankedSalaries AS (   SELECT Salary, ROW_NUMBER() OVER (ORDER BY Salary DESC) AS Rank   FROM Employees ) SELECT Salary AS SecondHighestSalary FROM RankedSalaries WHERE Rank = 2; --- 2. Write a query to calculate a running total of sales. SELECT   OrderID,   OrderDate,   Amount,   SUM(Amount) OVER (ORDER BY OrderDate) AS RunningTotal FROM Orders; --- 3. Retrieve customers who placed no orders using a LEFT JOIN. SELECT c.CustomerID, c.CustomerName FROM Customers c LEFT JOIN Orders o ON c.CustomerID = o.CustomerID WHERE o.OrderID IS NULL; --- 4. Write a query to find the top 3 highest salaries. SELECT DISTINCT Salary FROM Employees ORDER BY Salary DESC LIMIT 3; Using DENSE_RANK(): WIT...
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Product Manager tips & tricks + techniques

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Effective Techniques for Prioritizing Product Features To prioritize product features effectively, consider the following techniques commonly recommended in product management: 1. RICE Framework (Reach, Impact, Confidence, Effort): Reach: Estimate how many users will benefit from the feature. Impact: Assess the potential effect of the feature on the user experience or business goals. Confidence: Evaluate how certain you are about your reach and impact estimates. Effort: Measure the resources and time required to implement the feature. Calculate a score (Reach × Impact × Confidence ÷ Effort) to prioritize features. 2. MoSCoW Method: Categorize features into: Must-have: Critical for the product's success. Should-have: Important but not urgent. Could-have: Nice to have but not essential. Won’t-have: Not a priority for the current phase. 3. Kano Model: Classify features based on user satisfaction and implementation effort: Basic Needs: Must be included or the product will fail. Perform...
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UBI - Usage Based Insurance/InsurTech for Diverse BusinessTech Architecture Strategies and Accelerate Sales via Google Analytics GA4

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 UBI - Usage Based Insurance/InsurTech for Diverse BusinessTech Architecture Strategies and Accelerate Sales via Google Analytics GA4 Usage-Based Insurance (UBI) leverages data from customers' usage patterns (e.g., driving behavior) to calculate personalized premiums. This model benefits both insurers and customers by aligning pricing with actual risk levels. Key Business Components Telematics Integration : Collect real-time data from vehicle sensors, smartphones, or telematics devices. Data includes metrics like speed, braking, mileage, and time of usage. Personalized Pricing : Analyze driving patterns to determine risk and tailor insurance premiums accordingly. Offer dynamic pricing to incentivize safer behavior. Customer Engagement : Use behavioral insights to provide feedback, discounts, and additional insurance products. Sales and Marketing Optimization : Employ data-driven approaches to identify and target high-value customer segments. Leverage GA4 for funnel analysis, audie...
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Stock Market Real time dashboard in Google sheet

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Here’s the step-by-step process for creating a Google Sheets dashboard for real-time stock market data in a point-by-point format: --- Step 1: Setup the Google Sheet 1. Open a new Google Sheet. 2. Rename the sheet to something like "Stock Dashboard." --- Step 2: Enable Real-Time Data with GOOGLEFINANCE 1. Use the GOOGLEFINANCE function to fetch stock data. 2. Example formulas: Current Price: =GOOGLEFINANCE("TICKER_SYMBOL", "price") Opening Price: =GOOGLEFINANCE("TICKER_SYMBOL", "open") 52-Week High: =GOOGLEFINANCE("TICKER_SYMBOL", "high52") 52-Week Low: =GOOGLEFINANCE("TICKER_SYMBOL", "low52") Market Cap: =GOOGLEFINANCE("TICKER_SYMBOL", "marketcap") --- Step 3: Create Columns for Data 1. Add headers in Row 1: Stock Symbol Current Price Open Price 52W High 52W Low Market Cap 2. Enter stock symbols (e.g., "GOOG", "AAPL") in Column A. 3. Use the GOO...
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Diversified Investment on Nifties & Fractional Ownership with diverse cities

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Fractional Ownership  Investing ₹25 lakh in fractional ownership of commercial real estate across major Indian cities can yield varying returns based on rental yields and property appreciation rates. Here's a comparative analysis for Bangalore, Chennai, Mumbai, Delhi, Kolkata, Pune, and Hyderabad over a 10-year period: 1. Rental Yields and Property Appreciation Rates: Bangalore: Rental Yield: Approximately 7.75% per annum. Property Appreciation: Around 8% per annum.  Chennai: Rental Yield: Approximately 5.06% per annum. Property Appreciation: Around 6% per annum. Mumbai: Rental Yield: Approximately 7.75% per annum. Property Appreciation: Around 7% per annum.  Delhi: Rental Yield: Approximately 8% per annum. Property Appreciation: Around 6% per annum.  Kolkata: Rental Yield: Approximately 5.03% per annum. Property Appreciation: Around 5% per annum. Pune: Rental Yield: Approximately 4.35% per annum. Property Appreciation: Around 6% per annum.  Hyderabad: Rental Yi...
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