Data Warehouse 面接の質問と回答
質問 1. What is a Data Warehouse?
A Data Warehouse is a centralized repository that stores large volumes of structured and unstructured data from various sources. It is designed for query and analysis rather than transaction processing.
Example:
A company's data warehouse may store sales data, customer information, and other relevant data to support business intelligence and reporting.
質問 2. Explain the difference between OLAP and OLTP.
OLAP (Online Analytical Processing) is used for complex queries and data analysis, while OLTP (Online Transaction Processing) is focused on transactional processing and supports day-to-day business operations.
Example:
OLAP is used for generating reports and business intelligence, whereas OLTP is used for order processing and transaction recording.
質問 3. What is the star schema in a Data Warehouse?
The star schema is a type of dimensional modeling in which a central fact table is connected to dimension tables through foreign key relationships. It simplifies data retrieval for analytical queries.
Example:
In a retail data warehouse, the fact table may contain sales data, and dimension tables may include products, customers, and time.
質問 4. What is ETL in the context of Data Warehousing?
ETL (Extract, Transform, Load) is a process used to extract data from source systems, transform it into a usable format, and load it into a data warehouse for analysis and reporting.
Example:
Extracting customer data from a CRM system, transforming it to a standardized format, and loading it into a data warehouse for customer analytics.
質問 5. Explain the concept of slowly changing dimensions (SCD).
Slowly changing dimensions refer to the handling of changes in data over time, such as updating or inserting records in a dimension table to maintain historical information in a data warehouse.
Example:
Tracking changes in employee positions over time in a human resources data warehouse.
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