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Answer: Data modeling, which is crucial for defining how data is structured, related, and constrained within a database or data warehouse to support scalability and complex queries.
**Correct Answer: C. Data modeling** **Explanation:** Data modeling is essential in the design of a data system for defining the structure, relationships, and constraints of data within a database or data warehouse. It supports scalability and complex queries by: - **Identifying data entities**: Pinpointing the main objects or entities in the data. - **Determining attributes**: Figuring out the properties or features of each entity. - **Setting up relationships**: Establishing connections between entities (e.g., one-to-one, one-to-many). - **Designing data schemas**: Crafting the logical and physical layout of the database, including tables and indexes. **Incorrect Options:** - **A. Data collection**: This step is about gathering raw data from various sources and does not involve defining the structure or relationships. - **B. Data integration**: This involves merging data from different sources into a unified dataset but does not define the schema or relationships. - **D. Data pre-processing**: This phase is focused on cleaning and transforming data for analysis but does not involve defining the data schema or relationships.
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In the design of a data system for a large-scale e-commerce platform, the team is tasked with ensuring that the system can handle high volumes of transactions while maintaining data integrity and supporting complex queries for analytics. Which phase of the data system design is primarily dedicated to outlining the data schema, structures, and the relationships between them to meet these requirements? Choose one correct option.
A
Data collection, which involves gathering raw data from various sources without considering the structure or relationships.
B
Data integration, which focuses on merging data from different sources into a unified dataset but does not define the schema or relationships.
C
Data modeling, which is crucial for defining how data is structured, related, and constrained within a database or data warehouse to support scalability and complex queries.
D
Data pre-processing, which is about cleaning and transforming data for analysis but does not involve defining the data schema or relationships.
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