Foundations of Data Science

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Cardinality

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Foundations of Data Science

Definition

Cardinality refers to the uniqueness of data values contained in a particular field or column of a database table. It helps define relationships between tables and indicates how many instances of one entity relate to instances of another entity. This concept is essential in establishing the structure and integrity of a database, as it influences how data is organized, queried, and maintained.

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5 Must Know Facts For Your Next Test

  1. High cardinality means that a column has a large number of unique values, while low cardinality indicates fewer unique values.
  2. Understanding cardinality is crucial for optimizing database performance and ensuring efficient indexing strategies.
  3. In relational databases, cardinality determines how tables are related, influencing the design of the database schema.
  4. Different types of cardinality include one-to-one, one-to-many, and many-to-many relationships, each affecting data integrity in unique ways.
  5. Cardinality can impact the outcome of SQL queries and joins by determining how data from different tables is matched and retrieved.

Review Questions

  • How does cardinality affect the design of a relational database schema?
    • Cardinality plays a critical role in designing a relational database schema by defining how different tables relate to each other. It determines whether relationships are one-to-one, one-to-many, or many-to-many, which influences how data is organized and accessed. Properly identifying cardinality helps in creating efficient structures that ensure data integrity and optimal performance during queries.
  • Discuss the implications of high versus low cardinality on database performance and indexing.
    • High cardinality typically results in better query performance because it allows for more efficient indexing and reduces the likelihood of duplicate values. In contrast, low cardinality may lead to less efficient indexes since many records may point to the same value. Understanding these implications helps database designers choose appropriate indexing strategies that enhance overall database performance and minimize retrieval times.
  • Evaluate the importance of recognizing cardinality when creating SQL queries involving multiple tables.
    • Recognizing cardinality is essential when creating SQL queries involving multiple tables because it directly affects how the join conditions are structured. If cardinality is misunderstood, it can lead to incorrect results or inefficient queries that take longer to execute. For example, knowing whether a relationship is one-to-many or many-to-many influences how we write our joins and aggregate functions, ensuring accurate data retrieval from the involved tables.
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