Data Engineer 面试题与答案
问题 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.
问题 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.
问题 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.
问题 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.
问题 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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- What is a schema in the context of databases?
- Explain the concept of ETL in the context of data engineering.