DAA-C01 Question 69
Single answerLoad files using SnowsightA data analyst needs to quickly load a vendor-delivered CSV file from a local laptop into an existing Snowflake table for validation. The analyst is using Snowsight and wants the load process to correctly handle the file's first row as column headers rather than loading it as data. Which action should the analyst take in Snowsight during the load workflow?
- A
Create a task in Snowsight to skip the first row before loading the file
- B
In the Snowsight Load Data workflow, configure the file format or load settings to skip the header row
- C
Convert the target table to a temporary table before using Snowsight to load the file
- D
Use a worksheet to run SELECT with FILE_FORMAT => (PARSE_HEADER = TRUE) directly against the local file
Show answer and explanation
Correct answer: B
Explanation
When loading files through Snowsight, Snowflake uses a guided workflow that uploads the local file to an internal stage and then loads it into the target table. For CSV files that include a header row, the correct approach is to configure the file format or load setting to skip that row, typically using the CSV file format option SKIP_HEADER. This is a practical, common requirement when analysts use Snowsight for ad hoc validation loads. Best practice is to manage parsing behavior through file format settings rather than changing table type or introducing orchestration objects like tasks. Snowflake documentation on loading data and file formats for CSV files describes these options, including header-row handling during COPY-based ingestion workflows.
- A. Incorrect.
Incorrect. Tasks are used to schedule SQL statements or stored procedure executions; they are not the mechanism for interactively handling a local file upload in Snowsight. A common misconception is that preprocessing file rows in Snowflake requires orchestration objects, but for a straightforward upload through Snowsight, header handling is configured as part of the load/file format settings.
- B. Correct.
Correct. In Snowsight's data loading workflow, the analyst can define or select file format-related settings such as skipping header rows for CSV files. This is the appropriate way to ensure the first row, which contains column names, is not loaded as data. This aligns with Snowflake best practice: use file format options such as SKIP_HEADER for CSV ingestion behavior.
- C. Incorrect.
Incorrect. Whether the target table is permanent, transient, or temporary does not control how CSV header rows are interpreted during loading. Someone might choose this option if they confuse table lifecycle/storage behavior with file parsing behavior, but those are separate concerns.
- D. Incorrect.
Incorrect. PARSE_HEADER is not the standard solution for loading a local file through Snowsight into a table, and a local file cannot simply be queried directly from a worksheet without first being staged/uploaded. In practice, Snowsight's upload/load workflow handles local file staging and loading, and CSV header treatment is managed through load/file format settings such as SKIP_HEADER.