What are the ways to define schema? Difference between programmatic and declarative manner? Video 10

Описание: In this playlist series, I’ve explained key interview questions across several core data engineering topics like Azure Data Factory (ADF), PySpark, Databricks, Dimensional Modeling, and Performance Optimization. Each topic is explained in simple terms, making it easy for beginners to understand, while also diving into more advanced questions that are commonly asked in interviews. This series is perfect for anyone preparing for technical interviews or wanting to enhance their knowledge in these areas.

The series covers essential topics in ADF, such as what it’s used for, how to create pipelines, linked services, and the differences between Mapping Data Flows and Wrangling Data Flows. For PySpark, I’ve walked through how to set up a SparkSession, explained RDDs vs DataFrames, and provided tips on optimizing PySpark jobs. In Databricks, you’ll learn about Delta Lake architecture, implementing multi-hop architectures, and auto-scaling in clusters.

Additionally, I’ve included Dimensional Modeling concepts like handling slowly changing dimensions (SCD) Type 2, and performance optimization techniques for distributed joins and incremental data processing. This playlist is designed to give you both the fundamental knowledge and the advanced tips to ace your next interview!