DAA-C01必殺問題集 & DAA-C01最新対策問題

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Snowflake DAA-C01 Exam Syllabus Topics:

SectionObjectives
Snowflake Architecture and Data Platform Fundamentals- Snowflake architecture concepts
  • 1. Cloud services layer, compute layer, storage layer
    • 2. Virtual warehouses and scaling
      - Data platform fundamentals
      • 1. Separation of storage and compute
        • 2. Data lifecycle in Snowflake
          Security, Governance, and Data Sharing- Access control and security
          • 1. Authentication and encryption concepts
            • 2. Role-based access control (RBAC)
              - Data sharing and governance
              • 1. Data masking and policies
                • 2. Secure data sharing
                  Data Modeling and Performance Optimization- Performance tuning
                  • 1. Clustering and pruning techniques
                    • 2. Warehouse sizing and auto-suspend/auto-resume
                      - Modeling approaches in Snowflake
                      • 1. Data normalization vs denormalization
                        • 2. Star and snowflake schemas
                          Data Transformation and Analysis- SQL-based transformations
                          • 1. Semi-structured data (VARIANT, JSON, XML)
                            • 2. Joins, aggregations, window functions
                              - Analytical workloads
                              • 1. Materialized views and caching
                                • 2. Query optimization for analytics
                                  Data Loading and Unloading- Data export
                                  • 1. UNLOAD and external stages
                                    - Data ingestion methods
                                    • 1. Continuous ingestion and Snowpipe concepts
                                      • 2. COPY INTO and bulk loading

                                        >> DAA-C01必殺問題集 <<

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                                        Snowflake SnowPro Advanced: Data Analyst Certification Exam 認定 DAA-C01 試験問題 (Q27-Q32):

                                        質問 # 27
                                        Your company is using Snowflake to store customer transaction data'. You want to enrich this data with demographic information from a Snowflake Marketplace data provider. The provider offers a secure data share with a view called 'CUSTOMER DEMOGRAPHICS. You need to join the customer transaction data in your 'TRANSACTIONS' table with the demographic data from the 'CUSTOMER DEMOGRAPHICS' view. Which of the following SQL queries is the MOST efficient and secure way to achieve this, assuming you have already created a database from the share?

                                        正解：E

                                        解説：
                                        Option B is the most efficient and secure because it explicitly uses an INNER JOIN, ensuring that only matching records between the TRANSACTION table and the Customer Demographics view are included. Using INNER JOIN improves performance compared to implicit joins (Option A). Options C and E uses LEFT and FULL OUTER joins which might result in unnecessary nulls and impacting the perfromance. Option D will not work because the schema name is missing.


                                        質問 # 28
                                        When handling CSV, JSON, and Parquet data types for consumption, what advantages do Parquet files typically offer over the others?

                                        正解：C

                                        解説：
                                        Parquet files often provide better compression and query performance compared to CSV and JSON due to their columnar storage format, enhancing efficiency in handling large datasets.


                                        質問 # 29
                                        Why are Stored Procedures valuable in data analysis using SQL?

                                        正解：C

                                        解説：
                                        Stored Procedures aid in data analysis by enabling custom and repeated data operations, enhancing efficiency.


                                        質問 # 30
                                        When maintaining reports and dashboards, why is it essential to configure subscriptions and updates?

                                        正解：B

                                        解説：
                                        Subscriptions and updates ensure timely information delivery, a crucial aspect of maintaining reports and dashboards.


                                        質問 # 31
                                        A Directed Acyclic Graph (DAG) of 12 tasks (ETLDAILY) failed because one of the tasks failed (STEP10), therefore the dependent tasks (STEP11 and STEP12) did not run. Which command is needed to re-run task STEP10 and the two dependent tasks?

                                        正解：A

                                        解説：
                                        Managing complex pipelines involving multiple dependent tasks requires an understanding of Task Graphs (DAGs). In Snowflake, a DAG is a series of tasks with parent-child relationships. If a parent task (like STEP10) fails, Snowflake automatically cancels the execution of all child tasks (like STEP11 and STEP12) to prevent data corruption or inconsistent states.
                                        To recover from such a failure, Snowflake provides the RETRY LAST clause within the EXECUTE TASK command. The critical nuance here is that you do not target the individual failed task; instead, you target the root task of the graph (in this case, ETLDAILY). When you run EXECUTE TASK <root_task> RETRY LAST;, Snowflake identifies the most recent failed run of that graph and intelligently resumes execution starting from the failed task (STEP10) and continues through all subsequent dependent tasks that were previously skipped.
                                        Evaluating the Options:
                                        * Option A is incorrect because attempting to execute just STEP10 would treat it as a standalone run and would not automatically trigger the dependent logic of the ETLDAILY graph structure.
                                        * Options C and D are incorrect because RESUME is a DDL command used to change a task's state from SUSPENDED to STARTED (enabled). It does not trigger an immediate execution or a retry of a failed run; it merely allows the task to run on its next scheduled interval.
                                        * Option B is the 100% correct answer. It utilizes the dedicated Snowflake mechanism for graph recovery, ensuring that the entire pipeline is completed starting from the point of failure without re- running successfully completed earlier steps.


                                        質問 # 32
                                        ......

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