SnowPro DAA-C01 Übungsprüfungen
Zuletzt aktualisiert am 26.04.2025- Prüfungscode: DAA-C01
- Prüfungsname: Snowflake Certified SnowPro Advanced - Data Analyst
- Zertifizierungsanbieter: SnowPro
- Zuletzt aktualisiert am: 26.04.2025
How do materialized views differ from regular views in the context of data analysis?
- A . Regular views provide a persisted snapshot of data, unlike materialized views.
- B . Materialized views restrict data accessibility compared to regular views.
- C . Regular views offer precomputed snapshots, differentiating them from materialized views.
- D . Materialized views simplify complex data structures for ease of analysis, unlike regular views.
How do stored procedures contribute to data analysis efficiency in SQL compared to UDFs?
- A . UDFs enhance query performance more effectively than stored procedures.
- B . Stored procedures hinder customization in data operations.
- C . They enable the execution of repetitive tasks, enhancing efficiency.
- D . Stored procedures allow limited data accessibility for improved security.
How do partitioning strategies impact query performance and data storage efficiency in Snowflake?
- A . Partitioning improves query planning only
- B . Enhances query performance and reduces storage requirements
- C . Limits data access for specific user roles
- D . Reduces query performance and increases storage requirements
Which action is essential in performing exploratory ad-hoc analyses?
- A . Focusing solely on established trends without investigating anomalies
- B . Utilizing ad-hoc queries to examine patterns and anomalies
- C . Analyzing a small subset of the available data
- D . Relying solely on predefined queries without exploration
How can incorporating visualizations in reports and dashboards facilitate better data comprehension and analysis for business use scenarios?
- A . Visualizations don’t impact data comprehension or analysis significantly.
- B . Presenting data visually increases complexity in analysis.
- C . They enhance data comprehension, aiding effective analysis.
- D . Visualizations limit data exploration and analysis capabilities.
When maintaining reports and dashboards, why is it crucial to build automated and repeatable tasks?
- A . Automated tasks reduce manual efforts, ensuring consistency.
- B . Automated tasks increase the complexity of dashboard management.
- C . Repeatable tasks hinder data updates in dashboards.
- D . They ensure inconsistency in reports and dashboards.
What role does operationalizing data play in maintaining reports and dashboards for business requirements?
- A . It limits the usability of reports by narrowing down access.
- B . Operationalizing data ensures consistent and efficient usage.
- C . Operationalizing data complicates dashboard management.
- D . It restricts data updates, affecting dashboard accuracy.
How do row access policies and Dynamic Data Masking impact the creation of dashboards in terms of data visibility and security?
- A . Dynamic Data Masking doesn’t affect data visibility in dashboards.
- B . Both policies restrict data visibility for better security.
- C . They improve data visibility for all users without restrictions.
- D . Row access policies limit data visibility based on user privileges.
How does automating and implementing data processing contribute to the overall efficiency of data ingestion?
- A . Automating processing hampers data accuracy.
- B . Implementing data processing increases data redundancy.
- C . Automation eliminates human intervention, ensuring consistency.
- D . It slows down the data ingestion process significantly.
What critical role do user-defined functions (UDFs) play in SQL for advanced data analysis?
- A . UDFs hinder query optimization in SQL.
- B . UDFs only handle basic data manipulation tasks.
- C . They enable customized operations on data, extending SQL functionalities.
- D . UDFs are limited to specific data types.