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Snowflake SOL-C01 Prüfungsplan:

Thema	Einzelheiten
Thema 1	Identity and Data Access Management: This domain focuses on Role-Based Access Control (RBAC) including role hierarchies and privileges, along with basic database administration tasks like creating objects, transferring ownership, and executing fundamental SQL commands.
Thema 2	Data Protection and Data Sharing: This domain addresses continuous data protection through Time Travel and cloning, plus data collaboration capabilities via Snowflake Marketplace and private Data Exchange sharing.
Thema 3	Data Loading and Virtual Warehouses: This domain covers loading structured, semi-structured, and unstructured data using stages and various methods, virtual warehouse configurations and scaling strategies, and Snowflake Cortex LLM functions for AI-powered operations.
Thema 4	Interacting with Snowflake and the Architecture: This domain covers Snowflake's elastic architecture, key user interfaces like Snowsight and Notebooks, and the object hierarchy including databases, schemas, tables, and views with practical navigation and code execution skills.

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Snowflake Certified SnowPro Associate - Platform Certification SOL-C01 Prüfungsfragen mit Lösungen (Q49-Q54):

49. Frage
Which column is returned when the FLATTEN table function is executed?

A. OUTPUT
B. LEVEL
C. VALUE
D. ROWNUM

Antwort: C

Begründung:
The FLATTEN table function expands semi-structured data such as arrays or objects stored in VARIANT columns. Its output includes several metadata columns, and the most important among them isVALUE, which contains the extracted element from the array or object. VALUE is the column that developers typically join on or reference to access the flattened data.
In addition to VALUE, FLATTEN returns KEY (for object keys), INDEX (position in arrays), SEQ (internal ordering), and PATH (hierarchical reference path). These other columns support analytical or transformation logic, but VALUE remains the primary output used for downstream SQL.
The other listed options-OUTPUT, ROWNUM, and LEVEL-are not part of the FLATTEN function's output schema. ROWNUM and LEVEL may appear in other SQL contexts but not in FLATTEN results.
Therefore, the correct answer is VALUE.

50. Frage
What does the SELECT * statement do in a Snowflake query?

A. Retrieves all columns from a specified table or view
B. Retrieves only distinct values
C. Retrieves only the primary key column
D. Retrieves a limited number of rows

Antwort: A

Begründung:
The SELECT * statement instructs Snowflake to returnall columnsfrom the referenced table or view. This is commonly used during data exploration, debugging, initial data profiling, and validation steps. It allows users to quickly view the complete dataset structure without manually specifying each column name.
However, while SELECT * retrieves all columns, it does not limit the number of rows. To restrict rows, developers must include aLIMITclause (e.g., SELECT * FROM table LIMIT 10;).
The query does not automatically apply DISTINCT or primary key filtering-Snowflake returns all rows exactly as stored unless additional filtering, WHERE conditions, or ordering are provided.
Though SELECT * is convenient, Snowflake best practices recommend explicitly selecting columns in production workloads to optimize performance and avoid unnecessary scanning of unused fields.

51. Frage
Which of the following statements about External Tables in Snowflake are true?

A. External tables require a virtual warehouse to be online for data access.
B. External tables provide read-only access to data stored in external cloud storage locations.
C. Changes to the underlying files in the external stage are automatically reflected in the external table without any manual refresh.
D. External tables store data within Snowflake's internal storage.
E. External tables can be directly updated using standard SQL DML statements (INSERT, UPDATE, DELETE).

Antwort: A,B

Begründung:
Options C and D are correct. External tables provide read-only access to data residing in external cloud storage (e.g., Amazon S3, Azure Blob Storage, Google Cloud Storage), and they require a virtual warehouse to be online for querying the data. A is incorrect because external tables do not store data in Snowflake's internal storage. B is incorrect because external tables are read-only and cannot be directly updated with DML. E is incorrect because manual refreshing/metadata caching is required after changes to the source data.

52. Frage
Which of the following statements are true about Cortex functions?

A. They support multiple languages
B. They are limited to a specific domain
C. They can handle structured and semi-structured data
D. They can be combined to perform complex data processing tasks

Antwort: A,C,D

Begründung:
SnowflakeCortex functionsenable AI-powered operations directly within SQL and Python, supporting multiple languages via translation, classification, summarization, and document extraction functions. They operate seamlessly onstructuredandsemi-structureddata stored in VARIANT columns, allowing LLMs to process text, JSON, documents, and rich content.
Cortex functions can be combined within SQL pipelines-for example, using PARSE_DOCUMENT to extract data, followed by CLASSIFY_TEXT to categorize extracted fields, and then SUMMARIZE to produce narrative summaries. This composability enables sophisticated multi-stage workflows for document intelligence, support ticket analysis, compliance automation, and semantic enrichment.
They arenot limited to a single domain; Cortex functions apply to finance, retail, support operations, healthcare, legal analysis, and general AI-assisted data processing.
Thus, Cortex functions are versatile, multi-domain, multi-language tools integrated with Snowflake's compute and governance layers.

53. Frage
You have a table named 'CUSTOMER ORDERS with columns `customer id', `order date' , and
'order amount'. You want to retrieve the top 5 customers who placed orders on a specific date ('2023-01-15') based on the total order amount. Which SQL query will achieve this?

A. SELECT customer_id, AS total_amount FROM CUSTOMER_ORDERS GROUP BY customer_id WHERE order_date = '2023-01-15' ORDER BY total amount DESC LIMIT 5;
B. SELECT customer_id, AS total_amount FROM CUSTOMER_ORDERS WHERE order_date =
'2023-01-15' ORDER BY total_amount DESC LIMIT 5;
C. SELECT customer_id, order_amount FROM CUSTOMER_ORDERS WHERE order_date = '2023-
01-15' ORDER BY order_amount DESC LIMIT 5;
D. `sql SELECT TOP 5 customer_id, AS total_amount FROM CUSTOMER_ORDERS WHERE order_date = '2023-01-15' GROUP BY customer id ORDER BY total amount DESC;
E. SELECT customer_id, AS total_amount FROM CUSTOMER_ORDERS WHERE order_date =
'2023-01-15' GROUP BY customer_id ORDER BY total amount DESC LIMIT 5;

Antwort: E

Begründung:
Option A is the correct query. It filters the data for the specific date, groups the results by
`customer_id' to calculate the total order amount for each customer, orders the results in descending order based on the total amount, and then limits the output to the top 5 customers.
Option B has the WHERE clause in the wrong order. Option C misses the GROUP BY clause, resulting in only one row. Option D does not sum the order amounts. Option E is not valid Snowflake SQL; Snowflake does not use TOP clause. It is standard SQL to use the LIMIT clause.

54. Frage
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