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| Section | Objectives |
|---|---|
| Data Modeling and Performance Optimization | - Modeling approaches in Snowflake
|
| Snowflake Architecture and Data Platform Fundamentals | - Snowflake architecture concepts
|
| Security, Governance, and Data Sharing | - Data sharing and governance
|
| Data Transformation and Analysis | - SQL-based transformations
|
| Data Loading and Unloading | - Data export
|
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32. Frage
A Data Analyst needs to add address details based on a customer's latitude and longitude to a customer sales database. The Analyst found a free Worldwide Address Data listing on the Snowflake Marketplace. The ACCOUNTADMIN placed the data set into a new database called ADDRESS_DATA. The Data Analyst needs to join the ADDRESS_DATA.OPENADDRESS table with the ORDERS table which is stored in the GLOBAL_DWH database. The combined data set needs to be created as a view. How can this be achieved?
Antwort: B
Begründung:
This scenario highlights the rules governing Shared Databases and Cross-Database Joins in Snowflake.
When a user acquires data from the Snowflake Marketplace, it arrives in their account as a "Shared Database." A critical restriction of shared databases is that they are read-only. Users (including Data Analysts and even AccountAdmins) cannot create new objects-such as tables, schemas, or views-directly inside a database created from a share. Therefore, Options A, C, and D are architecturally impossible because they all involve trying to write a new view into the ADDRESS_DATA database.
To combine the shared data with internal data (like the ORDERS table in GLOBAL_DWH), the Analyst must create the view in a database where they have CREATE VIEW privileges and that is writeable. Since GLOBAL_DWH is an internal database owned by the organization, it is the appropriate location to host the logic that joins local data with external enrichment data.
Evaluating the Options:
* Option A and C are incorrect because you cannot create objects in a database created from a share.
* Option D is incorrect because while IMPORTED_PRIVILEGES are necessary to view the data, they do not grant the ability to create objects within the share.
* Option B is the 100% correct answer. By creating the view in the GLOBAL_DWH database (or any other local, non-shared database), the Analyst can successfully reference ADDRESS_DATA.
OPENADDRESS and GLOBAL_DWH.PUBLIC.ORDERS in a single SQL statement, effectively creating an enriched data layer for the organization.
33. Frage
A financial institution needs to build a dashboard to monitor fraudulent transactions. They have transaction data (amount, timestamp, location, merchant category), customer data (age, income, credit score), and fraud flags. They want to identify patterns and correlations that indicate potentially fraudulent activity. Which of the following visualizations and Snowflake features, when used in combination, would be MOST effective for this purpose? (Select TWO)
Antwort: D,E
Begründung:
Options B and D are the most effective. Option B utilizes an interactive dashboard with Power BI, incorporating geographical, temporal, and scatter plot visualizations to identify patterns. Anomaly detection algorithms in Snowflake further enhance the detection capabilities. Option D uses a heatmap to show correlations between key variables and implements interactive filters for detailed exploration. Implementing Row Access Policy would control data access, adding a security layer on top of sensitive financial data. Option A is not related to visualization or identifying correlations. Option C provides only a high-level summary. Option E involves exporting data outside Snowflake, which is less efficient and potentially less secure than using Snowflake's built-in capabilities.
34. Frage
You are tasked with creating a stored procedure in Snowflake to perform data cleansing on a table named 'CUSTOMER DATA'. The procedure should: 1) Remove rows where the 'EMAIL' column is NULL or empty. 2) Standardize the 'PHONE NUMBER' column by removing all non-numeric characters and ensuring it's exactly 10 digits long. 3) Return the number of rows removed due to invalid emails and the number of rows modified due to phone number standardization. Assume the table already exists and contains columns 'CUSTOMER (INT), (VARCHAR), and 'PHONE NUMBER (VARCHAR). Which of the following code snippets correctly implements this stored procedure? The procedure should use exception handling to gracefully handle errors, returning -1 for both counts if any error occurs.
Antwort: C
Begründung:
Option A is correct because it uses SQL to perform the data cleansing tasks, correctly utilizes 'SQLROWCOUNT' to capture the number of affected rows, and returns the results as a VARIANT OBJECT. It also includes proper exception handling. Options B, C, and D have errors in syntax or logic regarding return types, variable declaration, or how to retrieve row counts. Specifically, using Javascript or returning an ARRAY/TABLE when VARIANT is more flexible in this scenario.
35. Frage
A data analyst needs to forecast sales for the next quarter based on historical sales data'. The data is stored in a table named 'SALES DATA' with columns 'SALE DATE (DATE) and 'SALES_AMOUNT (NUMBER). The analyst wants to use the 'HOLT WINTERS function for forecasting, considering both trend and seasonality. However, the data contains some missing values for a few 'SALE DATE entries. Which of the following approaches is the MOST appropriate to handle missing data points while ensuring accurate forecasting with 'HOLT WINTERS in Snowflake?
Antwort: C
Begründung:
HOLT_WINTERS function requires continuous data for time series analysis, and missing values will lead to inaccurate forecasts. Option E is the most appropriate because Interpolation method such as linear interpolation will give you more precise result. Other approaches like direct use or Exclusion will result in wrong forecasting results.
36. Frage
When customizing data presentations in dashboards using filtering and editing techniques, what advantages do these methods offer? (Select all that apply)
Antwort: B,D
Begründung:
Customizing through filtering and editing enhances data accuracy and relevancy in dashboards.
37. Frage
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