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How to Become an Azure Data Engineer? 2023 Roadmap

Knowledge Hut

To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases. You should be able to create intricate queries that use subqueries, join numerous tables, and aggregate data.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines. Big Data Tools: Without learning about popular big data tools, it is almost impossible to complete any task in data engineering. This big data project discusses IoT architecture with a sample use case.

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AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses. In 2023, more than 5140 businesses worldwide have started using AWS Glue as a big data tool. Establish a crawler schedule.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Data pipelines must be scalable due to the volume of big data, which might fluctuate over time. The big data pipeline must process data in large volumes concurrently because, in reality, multiple big data events are likely to occur at once or relatively close together.

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A Beginner’s Guide to Learning PySpark for Big Data Processing

ProjectPro

RDDs are also fault-tolerant; thus, they will automatically recover in the event of a failure. RDD is an acronym for- Resilient - It is fault-tolerant and capable of regenerating data in the event of a failure. Distributed - The data in a cluster is distributed among the various nodes.

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100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms.