SOL-C01 Valid Test Pdf & SOL-C01 Reliable Test Simulator

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Snowflake SOL-C01 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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.
Topic 2
  • 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.
Topic 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.
Topic 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 Sample Questions (Q67-Q72):

NEW QUESTION # 67
What tasks can be performed using Snowflake Cortex AI? (Select TWO).

Answer: B,D

Explanation:
Snowflake Cortex AI provides built-in AI functions and tools designed to work natively with unstructured and structured data. Two key capabilities are:
* Extract and classify text using functions like PARSE_DOCUMENT, EXTRACT_TEXT, and classification models. Cortex can process documents, identify relevant fields, and convert unstructured content into usable structured formats.
* Simplify unstructured data workflows by combining document extraction, vector search, summarization, and AI reasoning tools (e.g., Cortex Analyst, Cortex Search) directly inside Snowflake without external services.
It does not provide Marketplace data sharing features, which belong to Snowflake's Data Sharing platform.
Loading semi-structured data is a core Snowflake capability using VARIANT and COPY INTO-not Cortex- specific. Enhancing data security is a platform-wide feature, not a Cortex function.


NEW QUESTION # 68
What information can be accessed using the Snowsight Monitoring tab?

Answer: D

Explanation:
The Snowsight Monitoring tab provides a centralized view of virtual warehouse usage metrics, enabling administrators and developers to evaluate how compute resources are being consumed. This includes critical insights such as credit usage, query load, concurrency levels, average queue times, execution durations, and auto-scaling activity (for multi-cluster warehouses). These metrics help determine whether a warehouse is correctly sized, whether concurrency issues are occurring, or whether workloads require scaling up or adding clusters.
Query history is available in a different section-"Activity # Query History"-not under Monitoring. Time Travel snapshots are not visualized within Monitoring; Time Travel is controlled via retention parameters and accessed with SQL (AT/BEFORE clauses). Schema change history is also not part of Monitoring and instead is discoverable through ACCOUNT_USAGE or specific metadata views.
The Monitoring tab exists specifically to help evaluate warehouse performance and resource consumption, enabling optimization of compute spending and better workload management.


NEW QUESTION # 69
Which function would you use to determine the sentiment of a customer review in Snowflake Cortex?

Answer: D

Explanation:
The SENTIMENT function in Snowflake Cortex analyzes text and returns a numerical sentiment score between -1 and 1. This value indicates whether the text expresses negative, positive, or neutral sentiment. It accepts English-language text and uses Snowflake's managed AI models to infer polarity based on contextual understanding. A negative score represents negative emotion, a positive score represents positive emotion, and values near zero indicate neutrality. It is ideal for customer reviews, feedback analysis, and text mining.
TRANSLATE is used for language translation, COMPLETE for text generation, and PARSE_DOCUMENT for extracting text from documents-not sentiment analysis. SENTIMENT provides fast, in-database AI inference without external model hosting or integration.


NEW QUESTION # 70
A data engineer needs to create a table named 'EMPLOYEES in the `PUBLIC' schema of the database 'COMPANY DATA'. The table should store employee IDs as integers, names as strings, and hire dates as dates. Which of the following SQL statements correctly creates this table?

Answer: D

Explanation:
The correct answer is E. It uses 'CREATE OR REPLACE to avoid errors if the table exists, specifies the full table name with database and schema ('COMPANY_DATA.PUBLIC.EMPLOYEES'), and uses appropriate data types: 'INT' for integers,
'VARCHAR(255)' for strings, and 'DATE for dates. Option A would cause errors if table already exists, Option B and C does not specify the database and schema. Option D uses NUMBER datatype.


NEW QUESTION # 71
What is the primary purpose of the LIMIT clause in a Snowflake query?

Answer: D

Explanation:
The LIMIT clause limits the number of rows Snowflake returns from a query. It is commonly used to preview datasets, improve performance when exploring large tables, and paginate results. LIMIT may be combined with OFFSET to skip a number of rows. Sorting is performed with ORDER BY, filtering with WHERE, and grouping with GROUP BY-not with LIMIT. Therefore, restricting returned rows is the primary purpose of LIMIT.


NEW QUESTION # 72
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