Remove Data Schemas Remove Datasets Remove Relational Database
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AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

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This serverless data integration service can automatically and quickly discover structured or unstructured enterprise data when stored in data lakes in Amazon S3, data warehouses in Amazon Redshift, and other databases that are a component of the Amazon Relational Database Service.

AWS 66
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50 PySpark Interview Questions and Answers For 2025

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With the global data volume projected to surge from 120 zettabytes in 2023 to 181 zettabytes by 2025, PySpark's popularity is soaring as it is an essential tool for efficient large scale data processing and analyzing vast datasets. Resilient Distributed Datasets (RDDs) are the fundamental data structure in Apache Spark.

Hadoop 68
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How to Crack Amazon Data Engineer Interview in 2025?

ProjectPro

Managing data quality issues in ETL (Extract, Transform, Load) processes is crucial for ensuring the reliability of the transformed data. This involves a systematic approach that begins with data profiling to understand and identify anomalies in the dataset, including outliers and missing values.

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Top 15 Azure Databricks Interview Questions and Answers For 2025

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The distributed collection of structured data is called a PySpark DataFrame. They are stored in named columns and are equivalent to relational database tables. Various sources, including Structured Data Files, Hive Tables, external databases, existing RDDs, etc., How does PySpark DataFrames work?

Scala 40
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A 2025 Guide to Ace the Netflix Data Engineer Interview

ProjectPro

The transformation of unstructured data into a structured format is a methodical process that involves a thorough analysis of the data to understand its formats, patterns, and potential challenges. Master Data Engineering at your Own Pace with Project-Based Online Data Engineering Course !

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100+ Big Data Interview Questions and Answers 2025

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Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

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Top 25 DBT Interview Questions and Answers for 2025

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DBT (Data Build Tool) can handle incremental data loads by leveraging the incremental model , which allows only new or changed data to be processed and transformed rather than reprocessing the entire dataset. What techniques do you use to minimize run times when dealing with large datasets?