Star vs Snowflake Schema Types Quiz
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Questions and Answers

What is the central component of a star schema?

  • The foreign keys
  • The fact table (correct)
  • The query reporting attributes
  • The dimension tables
  • What is the primary purpose of the fact table in a star schema?

  • To support ad-hoc information needs
  • To store the decision analysis attributes (correct)
  • To contain classification and aggregation information
  • To link to the dimension tables via foreign keys
  • What is the relationship between the dimension tables and the fact table in a star schema?

  • Many-to-many
  • One-to-many (correct)
  • One-to-one
  • Many-to-one
  • Which of the following best describes the purpose of dimension tables in a star schema?

    <p>To provide classification and aggregation information</p> Signup and view all the answers

    How are dimensions used in querying a star schema?

    <p>To aggregate the numerical values in the fact table</p> Signup and view all the answers

    Which of the following is not a main characteristic of a star schema?

    <p>The dimension tables have a many-to-many relationship with the fact table</p> Signup and view all the answers

    What is a key characteristic of a Star schema?

    <p>Fact table surrounded by dimension tables</p> Signup and view all the answers

    Which type of schema design involves expanding dimension tables into multi-tables?

    <p>Snowflake Schema</p> Signup and view all the answers

    What does a Multi-fact star model represent in dimensional modeling?

    <p>Multiple fact tables surrounded by dimensions</p> Signup and view all the answers

    Why is a Star schema considered to have a simple design compared to a Snowflake schema?

    <p>Deals with less data redundancy</p> Signup and view all the answers

    In the context of dimensional modeling, what is a common characteristic of fact tables?

    <p>Contain detailed business events such as sales and expenses</p> Signup and view all the answers

    Why are conformed dimensions important in multi-fact star models?

    <p>To reduce the number of joins required in queries</p> Signup and view all the answers

    What are the two types of columns found in fact tables in dimensional modeling?

    <p>Keys and measures</p> Signup and view all the answers

    What is the grain of a measurement in a fact table?

    <p>The level of detail in the measurement</p> Signup and view all the answers

    What does the key column in a fact table consist of?

    <p>Foreign keys to dimensional tables</p> Signup and view all the answers

    In a dimensional model, where is ninety-percent of the data typically located?

    <p>Fact tables</p> Signup and view all the answers

    Which type of relationship exists between fact tables and dimensions in dimensional modeling?

    <p>One-to-many</p> Signup and view all the answers

    What is the purpose of the measures in a fact table?

    <p>Represent actual business activity</p> Signup and view all the answers

    Study Notes

    Star Schema

    • A star schema consists of a central fact table surrounded by dimension tables, connected via foreign keys.
    • The fact table contains a large number of rows corresponding to observed facts and external links.
    • The fact table contains descriptive attributes for decision analysis and query reporting, and foreign keys to link to dimension tables.

    Fact Table

    • Contains performance measures, operational metrics, and aggregated measures (e.g., sales volumes, customer retention rates, profit margins).
    • Primarily addresses what the data warehouse supports for decision analysis.
    • Contains two types of columns: keys and measures.

    Keys in Fact Table

    • Consist of a group of foreign keys (FK) that point to the primary keys of dimensional tables.
    • Enable business analysis.

    Measures in Fact Table

    • Represent actual measures of business activity (e.g., sales revenue, order quantity).
    • Each measurement has a grain, which is the level of detail in the measurement of an event (e.g., unit of measure, currency used, ending daily balance).
    • Examples: SalesQuantity, SalesAmount, ReturnAmount, ReturnQuantity, DiscountAmount, DiscountQuantity, and TotalCost.

    Dimension Tables

    • Contain classification and aggregation information about the central fact rows.
    • Contain attributes that describe the data contained within the fact table.
    • Address how data will be analyzed and summarized.
    • Have a one-to-many relationship with rows in the central fact table.

    Dimension Characteristics

    • Represented by one table in a star schema.
    • De-normalized data structure.
    • High level of data redundancy.
    • Maintenance is difficult.
    • Good for datamarts with simple relationships (1:1 or 1:many).

    Multi-fact Star Models

    • Examples of dimensional models depict a single fact table surrounded by dimensions, but reality requires multiple facts.
    • Multiple facts are often necessary (e.g., sales, expenses, inventory, and other business events).
    • Shared dimensions are referred to as conformed dimensions.

    Fact Table Characteristics

    • A fact is also referred to as an organizational performance measure.
    • Fact contains redundancy.
    • Ninety-percent of the data in a dimensional model is typically located in the fact tables.
    • Key design concerns include minimizing and standardizing data, and making it consistent.

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    Description

    Test your knowledge on the differences between Star and Snowflake Schema types in database design. Identify key characteristics such as data structure, complexity, and normalization levels.

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