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Data Engineer preguntas y respuestas de entrevista

Pregunta 16. What is Apache Spark, and how is it used in data processing?

Apache Spark is an open-source, distributed computing system used for big data processing and analytics. It supports in-memory processing and provides APIs for various programming languages.

Example:

Using Apache Spark to process large-scale log data and extract meaningful insights in near real-time.

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Pregunta 17. Explain the concept of data deduplication in data engineering.

Data deduplication involves identifying and removing duplicate records or data points within a dataset, improving data quality and storage efficiency.

Example:

Identifying and eliminating duplicate customer records in a CRM database.

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Pregunta 18. What are NoSQL databases, and when would you choose to use them over traditional relational databases?

NoSQL databases are non-relational databases designed for scalability, flexibility, and handling large amounts of unstructured or semi-structured data. They are chosen when dealing with high-volume, distributed, and dynamic data.

Example:

Using a NoSQL database to store and retrieve JSON documents in a web application.

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Pregunta 19. How do you handle data skew in a distributed computing environment?

Data skew occurs when certain partitions or shards have significantly more data than others. Techniques to handle data skew include re-partitioning, data pre-processing, and using advanced algorithms for data distribution.

Example:

Re-partitioning a dataset based on a different key to distribute the data more evenly in a Spark job.

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Pregunta 20. What is the role of data cataloging in a data ecosystem?

Data cataloging involves organizing and managing metadata about data assets in an organization. It helps in discovering, understanding, and governing data across the enterprise.

Example:

Using a data catalog to search for and understand the metadata of a specific dataset within an organization.

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