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| Section | Objectives |
|---|---|
| Data Transformation and Analysis | - SQL-based transformations
|
| Snowflake Architecture and Data Platform Fundamentals | - Data platform fundamentals
|
| Security, Governance, and Data Sharing | - Data sharing and governance
|
| Data Modeling and Performance Optimization | - Modeling approaches in Snowflake
|
| Data Loading and Unloading | - Data ingestion methods
|
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NEW QUESTION # 17
You have two tables in Snowflake: 'ORDERS and 'CUSTOMERS. The 'ORDERS' table contains information about customer orders, including 'ORDER ID', 'CUSTOMER ID', 'ORDER DATE, and 'ORDER AMOUNT. The 'CUSTOMERS table contains information about customers, including 'CUSTOMER ID', 'CUSTOMER NAME' , and 'CUSTOMER ADDRESS'. You need to create a view that joins these two tables based on 'CUSTOMER ID and includes only orders placed in the last 30 days. You also want to ensure that the view leverages the primary key information defined on the 'CUSTOMERS' table (even though Snowflake doesn't enforce it) for potential query optimizations. Which of the following SQL statements is the MOST efficient and best practice approach, considering Snowflake's optimizer?
Answer: C
Explanation:
Using 'CREATE OR REPLACE SECURE VIEW' is the best practice. 'CREATE OR REPLACE' allows you to update the view definition if needed without dropping and recreating it, minimizing disruption. A 'SECURE VIEW' prevents users from seeing the underlying query logic or accessing the base tables directly, enhancing security. The explicit JOIN syntax is preferred over the older implicit join syntax (option B). Snowflake's optimizer will leverage defined primary key relationships to optimize the join, even though it doesn't enforce them. Explicitly referencing schema isn't needed unless dealing with ambiguous names across schemas. The WHERE clause correctly filters for orders in the last 30 days.
NEW QUESTION # 18
You're working with a large dataset containing website user activity, including 'session_id', 'user_id', 'timestamp', and 'page_view'. You suspect bot activity is skewing your engagement metrics. Bots tend to have very short session durations and high page view counts within those sessions. Which of the following Snowflake SQL queries, used in combination, would be MOST effective in identifying and flagging potential bot sessions, considering performance on a large dataset? Assume you have access to Snowflake's statistical functions.
Answer: A
Explanation:
Option E is most effective because it identifies bot sessions based on two distinct criteria: unusually high page view counts AND unusually short session durations, which are characteristic of bots. By combining these two conditions with standard deviations, it reduces the likelihood of false positives. All other answer choices only check rate and not the count or session duration .
NEW QUESTION # 19
When managing Snowsight dashboards, what role do subscriptions and updates play in meeting business requirements?
Answer: A
Explanation:
Subscriptions and updates ensure timely information delivery, meeting business requirements.
NEW QUESTION # 20
When customizing data presentations in dashboards through filtering and editing techniques, what benefits do these methods offer? (Select all that apply)
Answer: C,D
Explanation:
Customization through filtering and editing enhances data accuracy and relevancy in dashboards.
NEW QUESTION # 21
You need to load data from a set of CSV files located in an AWS S3 bucket into a Snowflake table called 'SALES DATA. The CSV files have a header row, and you want to automatically detect the data types of the columns. However, some files might have inconsistent data types (e.g., a column that is usually an integer might occasionally contain a string). Furthermore the file are compressed using GZIP. Which of the following COPY INTO command options can you use to achieve this goal while handling potential data type mismatches?
Answer: C
Explanation:
The 'ON_ERROR = 'SKIP_RECORD" option allows the COPY INTO command to skip individual records that have data type mismatches or other errors during the load process. This ensures that the load process continues even if some records fail validation. 'SKIP_FILE' would skip entire file, 'CONTINUE' will only continue the process with the given data, and 'SKIP_FILE' skips the file. The VALIDATE UTF8 isn't directly relevant to data type issues
NEW QUESTION # 22
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