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Data Engineer preguntas y respuestas de entrevista

Pregunta 1. What is the difference between a database and a data warehouse?

A database is designed for transactional processing, while a data warehouse is optimized for analytical processing.

Example:

In a retail system, a database may store customer orders, while a data warehouse aggregates sales data for business intelligence.

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Pregunta 2. Explain the concept of ETL in the context of data engineering.

ETL stands for Extract, Transform, Load. It involves extracting data from source systems, transforming it into a usable format, and loading it into a target system.

Example:

Extracting customer data from a CRM system, transforming it into a standardized format, and loading it into a data warehouse.

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Pregunta 3. What is a schema in the context of databases?

A schema defines the structure of a database, including tables, fields, and relationships between tables.

Example:

In a relational database, a schema might include tables for 'users' and 'orders,' with defined fields for each.

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Pregunta 4. How do you handle missing or incomplete data in a dataset?

Methods to handle missing data include imputation (replacing missing values), deletion of rows or columns with missing data, or using advanced techniques like predictive modeling.

Example:

Replacing missing age values in a dataset with the mean age of the available data.

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Pregunta 5. Explain the concept of partitioning in a distributed database.

Partitioning involves dividing a large table into smaller, more manageable parts based on certain criteria. It helps in parallel processing and efficient data retrieval.

Example:

Partitioning a table based on date, so each partition contains data for a specific time range.

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