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[Hardware] Professional DAA-C01 Latest Test Online | Newest DAA-C01 Exam Topics and Correct

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【Hardware】 Professional DAA-C01 Latest Test Online | Newest DAA-C01 Exam Topics and Correct

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Snowflake SnowPro Advanced: Data Analyst Certification Exam Sample Questions (Q62-Q67):NEW QUESTION # 62
Which aspects are crucial for making predictions based on data for forecasting purposes? (Select all that apply)
  • A. Using only basic arithmetic functions for forecasting
  • B. Considering trends and anomalies in historical data
  • C. Relying solely on historical data without considering external factors
  • D. Incorporating statistical methods for accurate predictions
Answer: B,D
Explanation:
Incorporating statistical methods and considering trends/anomalies are crucial for accurate predictions in forecasting.

NEW QUESTION # 63
You need to create a dashboard for a logistics company to track delivery performance. The dashboard should display the following information: (1) Total number of deliveries per day, (2) Percentage of deliveries completed on time, (3) Average delivery time per city, (4) Number of deliveries exceeding the SLA (Service Level Agreement) by more than 1 hour. Which of the following chart combinations would be MOST effective to display this information in a clear and concise manner?
  • A. Line chart for total deliveries per day, pie chart for percentage of on-time deliveries, bar chart for average delivery time per city, and a table showing deliveries exceeding SLA
  • B. Time series chart for total deliveries per day, scorecard for percentage of on-time deliveries, geographical map with color-coded cities for average delivery time, and a table showing deliveries exceeding SLA.
  • C. Bar chart for total deliveries per day, scorecard for percentage of on-time deliveries, geographical map with color-coded cities for average delivery time, and a table showing deliveries exceeding SLA.
  • D. Time series chart for total deliveries per day, gauge chart for percentage of on-time deliveries, a heat grid showing city vs average delivery time, and a bullet chart for deliveries exceeding SLA target.
  • E. Area chart for total deliveries per day, scorecard for percentage of on-time deliveries, geographical map with color-coded cities for average delivery time, and a bar chart for deliveries exceeding SLA.
Answer: B
Explanation:
A Time series chart is best for showing trends over time (total deliveries per day). A scorecard provides a concise view of a key metric (percentage of on-time deliveries). A geographical map with color-coded cities effectively visualizes location-based data (average delivery time per city). A table provides detailed information on specific instances (deliveries exceeding SLA). Pie Charts are less ideal for percentage since it can be achieved better using Scorecard, heat grid not the best choice when geo is involved and it is less readable.

NEW QUESTION # 64
Which query will provide this data without incurring additional storage costs?
  • A. CREATE TABLE DEV.PUBLIC.TRANS_HIST AS (SELECT * FROM PROD.PUBLIC.
    TRANS_HIST);
  • B. CREATE TABLE DEV.PUBLIC.TRANS_HIST AS (SELECT * FROM PROD.PUBLIC.TRANS_HIST WHERE extract(year from (TRANS_DATE)) = 2019);
  • C. CREATE TABLE DEV.PUBLIC.TRANS_HIST LIKE PROD.PUBLIC.TRANS_HIST;
  • D. CREATE TABLE DEV.PUBLIC.TRANS_HIST CLONE PROD.PUBLIC.TRANS_HIST;
Answer: D
Explanation:
Snowflake utilizes a unique architecture known as Zero-Copy Cloning, which allows users to create a replica of a table, schema, or entire database without physically duplicating the underlying data files (micro- partitions). When you execute the CLONE command, Snowflake simply creates new metadata that points to the existing micro-partitions of the source object.
Because the data is not physically copied, the clone operation is nearly instantaneous and, crucially, incurs no additional storage costs at the moment of creation. Storage costs only begin to accumulate for the clone when the data in the source or the clone diverges-for example, if rows are updated or deleted in the clone, Snowflake creates new micro-partitions to store the changed data while preserving the original state in the source.
Evaluating the Options:
* Option A (LIKE) only copies the column definitions and structure of the table. It does not copy the data itself, so while it doesn't incur storage, it also doesn't provide the "data" requested by the prompt.
* Option B (CTAS - Create Table As Select) performs a full deep copy of the data. This creates entirely new micro-partitions, which immediately increases the storage footprint and associated costs.
* Option D is a filtered CTAS operation. While it may result in less data than the full table, it still involves creating new physical storage for the 2019 records, thus incurring additional costs.
* Option C is the 100% correct answer. It uses the CLONE keyword, which is the specific Snowflake feature designed to provide a full dataset for dev/test environments with zero initial storage impact. This is a core competency in the Data Transformation and Data Modeling domain.

NEW QUESTION # 65
An organization needs to provide daily summaries of key metrics to its executive team via email. They currently have a complex SQL query that generates the report, but the query takes several minutes to run. The executive team needs the data before 8 AM daily. The data warehouse is also used for other reporting and analytics tasks throughout the day. Given these constraints, what is the MOST efficient and reliable approach to operationalize this report?
  • A. Create a materialized view based on the complex SQL query. Schedule a task to refresh the materialized view nightly before 8 AM. Create a separate, simpler query against the materialized view to generate the report and email it.
  • B. Schedule a Snowflake task to execute the complex SQL query directly and email the results using Snowflake's email integration. Ensure the task runs on a large warehouse.
  • C. Use Snowflake's Data Marketplace to find a pre-built reporting solution that matches their requirements.
  • D. Create a Snowpipe to continuously ingest data into a separate table. Write a simplified SQL query on the target table to generate the report. Schedule a task to execute the query and email the results.
  • E. Use a third-party ETL tool to extract the data, transform it, and generate the report. Schedule the ETL job to run nightly and email the report.
Answer: A
Explanation:
Creating a materialized view (B) is the most efficient approach. Materialized views pre-compute the results, so the nightly task refreshes the pre-calculated data. This ensures fast report generation before 8 AM, even with a complex underlying query. Running the complex query directly (A) might exceed the time limit. Using a third-party ETL tool (C) adds unnecessary complexity. Snowpipe (D) is for continuous data ingestion, not report generation. Data Marketplace (E) is unlikely to perfectly match the custom needs.

NEW QUESTION # 66
Why is the Parquet format preferred for complex data sets?
  • A. It changes data colors for differentiation
  • B. It has visually appealing data presentation
  • C. It supports efficient compression and encoding schemes
  • D. It randomly alters data for testing
Answer: C

NEW QUESTION # 67
......
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