Before data cleansing, defining a schema serves to describe how the data is organized. Which option describes this best?

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Multiple Choice

Before data cleansing, defining a schema serves to describe how the data is organized. Which option describes this best?

A schema defines the structure of the data—the fields, data types, relationships between tables, and any constraints that govern values. This gives a clear map of how data is organized, which is essential when cleansing because you know what valid values and formats look like for each field and how records relate to one another. For example, knowing that a dataset has fields like id, name, email, and signup_date tells you to expect numeric IDs, properly formatted emails, and dates, so you can spot anomalies during cleaning. The other options describe outcomes that come from using and enforcing structure (like speeding up search with indexing, or controlling who can access data), but they don’t capture the primary purpose of defining how data is organized.

A schema defines the structure of the data—the fields, data types, relationships between tables, and any constraints that govern values. This gives a clear map of how data is organized, which is essential when cleansing because you know what valid values and formats look like for each field and how records relate to one another. For example, knowing that a dataset has fields like id, name, email, and signup_date tells you to expect numeric IDs, properly formatted emails, and dates, so you can spot anomalies during cleaning. The other options describe outcomes that come from using and enforcing structure (like speeding up search with indexing, or controlling who can access data), but they don’t capture the primary purpose of defining how data is organized.

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