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Data Warehouse Interview Questions And Answers | Data Warehouse Tutorial | Edureka Video Lecture | Learn the Fundamentals: Data Warehouse and Mining (English) - Data & Analytics
FAQs on Data Warehouse Interview Questions And Answers - Data Warehouse Tutorial - Edureka Video Lecture - Learn the Fundamentals: Data Warehouse and Mining (English) - Data & Analytics
| 1. What is a data warehouse? |  |
Ans. A data warehouse is a large and centralized repository of data that is used to support business intelligence and reporting activities. It is designed to store and organize data from various sources in a way that facilitates analysis and decision-making.
| 2. What is the difference between a data warehouse and a database? | |
Ans. While both a data warehouse and a database store data, they serve different purposes. A database is designed for transactional processing and day-to-day operations, whereas a data warehouse is optimized for analytical processing and reporting. Data warehouses often contain historical and aggregated data, while databases focus on real-time and detailed data.
| 3. What are the key components of a data warehouse architecture? | |
Ans. A data warehouse architecture typically consists of the following components:
- Data sources: These are the systems and databases from which data is extracted.
- ETL (Extract, Transform, Load) process: This is the process of extracting data from various sources, transforming it into a suitable format, and loading it into the data warehouse.
- Data storage: This is where the data is stored in a structured and organized manner.
- Data access: This includes tools and technologies that enable users to retrieve and analyze the data.
- Metadata: This is the information about the data in the data warehouse, such as its source, meaning, and quality.
| 4. What are the advantages of using a data warehouse? | |
Ans. Some of the advantages of using a data warehouse include:
- Improved data quality and consistency: Data is transformed and cleansed during the ETL process, ensuring high-quality and consistent data.
- Enhanced data analysis: The structured and organized nature of data warehouses allows for easier and faster analysis, leading to better decision-making.
- Historical analysis: Data warehouses store historical data, allowing users to analyze trends, patterns, and historical performance.
- Integration of disparate data sources: Data warehouses can integrate data from various sources, enabling a holistic view of the business.
- Performance optimization: Data warehouses are optimized for analytical processing, resulting in faster query performance.
| 5. What are some best practices for designing a data warehouse? | |
Ans. Some best practices for designing a data warehouse include:
- Clearly define the business requirements and objectives before designing the data warehouse.
- Design a scalable and flexible architecture that can accommodate future growth and changes.
- Use a star or snowflake schema to organize the data for easier analysis.
- Implement proper data modeling techniques to ensure data integrity and consistency.
- Regularly update and maintain the data warehouse to ensure data accuracy and freshness.
- Provide appropriate security measures to protect sensitive data.
- Involve end-users and stakeholders throughout the design and development process to ensure the data warehouse meets their needs.
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Dec 23, 2024 Last updated |
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