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Showing posts with the label Power BI Developer Interview question at Novartis

Meesho PySpark Interview Questions for Data Engineers in 2025

Meesho PySpark Interview Questions for Data Engineers in 2025 Preparing for a PySpark interview? Let’s tackle some commonly asked questions, along with practical answers and insights to ace your next Data Engineering interview at Meesho or any top-tier tech company. 1. Explain how caching and persistence work in PySpark. When would you use cache() versus persist() and what are their performance implications? Answer : Caching : Stores data in memory (default) for faster retrieval. Use cache() when you need to reuse a DataFrame or RDD multiple times in a session without specifying storage levels. Example: python df.cache() df.count() # Triggers caching Persistence : Allows you to specify storage levels (e.g., memory, disk, or a combination). Use persist() when memory is limited, and you want a fallback to disk storage. Example: python from pyspark import StorageLevel df.persist(StorageLevel.MEMORY_AND_DISK) df.count() # Triggers persistence Performance Implications : cache() is ...

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Power BI Developer Interview at Novartis: My Approach to the Questions

Power BI Developer Interview at Novartis: My Approach to the Questions Excited to share how I would answer the questions asked in a recent interview for a Power BI Developer role at Novartis. These questions cover both technical concepts and practical applications, so let’s dive in! 1️⃣ Introduce Yourself Answer: I’m a passionate data professional with [X years] of experience in data visualization, analytics, and reporting. I specialize in Power BI, SQL, and Python, having worked on projects involving dashboard creation, data modeling, and KPI analysis to drive business insights. My experience includes collaborating with cross-functional teams and delivering actionable insights for data-driven decision-making. 2️⃣ Explain Merge and Append Queries Answer: Merge Queries: Used to join two tables based on a common column (like SQL joins). It’s useful for combining data from different sources. Append Queries: Used to stack or union tables vertically, adding rows from one table to another....

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