DAA-C01 Dumps (V8.02) – Practice the Latest DAA-C01 Questions to Prepare for the SnowPro Advanced: Data Analyst Certification Exam

1. Which aspects are important when making predictions based on data for forecasting purposes? (Select all that apply)

2. When cleaning data, what role does using clones play in specific use-cases?

3. In what way can regular views be advantageous in data analysis?

4. When performing a descriptive analysis using Snowsight dashboards, how do they assist in summarizing large data sets?

5. How does performing data discovery through querying tables in Snowflake aid in data preparation?

6. How can stored procedures be beneficial in data analysis using SQL?

7. How can User-Defined Functions (UDFs) be utilized in SQL for data analysis?

8. How does leveraging partition pruning enhance query performance in Snowflake?

9. When managing Snowsight dashboards, what role do subscriptions and updates play in meeting business requirements?

10. Which statement accurately describes the usage of materialized views in data analysis?

11. When customizing data presentations in dashboards using filtering and editing techniques, what advantages do these methods offer? (Select all that apply)

12. When selecting data for building dashboards, which factors should be considered to ensure relevance and usability? (Select all that apply)

13. In data modeling for BI requirements, when is it preferable to use a flattened data set instead of a data model?

14. In data presentations for business use analyses, what significance do identifying patterns and trends hold?

15. What role does operationalizing data play in maintaining reports and dashboards for business requirements?

16. In Snowsight, what is the significance of creating diverse chart types (e.g., bar charts, scatter plots, heat grids) for data visualization?

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

18. How do Snowsight dashboards facilitate the presentation of data for business use analyses?

19. When loading data into Snowflake using Snowsight, what functionalities does this method offer? (Select all that apply)

20. What actions are involved in data discovery to identify necessary elements from available datasets in Snowflake? (Select all that apply)

21. How do secure views enhance data analysis practices?

22. When employing different modeling techniques for the consumption layer in Snowflake (e.g., dimensional, Data Vault), what factors influence the choice between these techniques?

23. How can incorporating visualizations in reports and dashboards facilitate better data comprehension and analysis for business use scenarios?

24. When maintaining reports and dashboards, why is it essential to build automated and repeatable tasks?

25. Identify the correct action involved in performing an exploratory ad-hoc analysis.

26. How does incorporating visualizations in reports and dashboards aid in presenting data for business use analyses?

27. When enriching data with Snowflake Marketplace, what role do data shares play in joining external data with existing datasets?

28. In Snowflake, how does Time Travel feature assist in data retrieval and analysis?

29. How do Materialized views differ from Regular views in the context of data analysis?

30. Which statistical method is commonly used in forecasting based on historical data?

31. When performing forecasting using statistics and built-in functions, what role do these functions play?

32. What actions are involved in performing general DML (Data Manipulation Language) operations in Snowflake? (Select all that apply)

33. When connecting BI tools to Snowflake for dashboard creation, what factors need to be considered for seamless integration? (Select all that apply)

34. When optimizing query performance in Snowflake, what benefits does result caching provide?

35. When utilizing geospatial functions in Snowflake, what functionalities do these functions offer? (Select all that apply)

36. Which actions are pertinent in identifying demographics and relationships during diagnostic analysis? (Select all that apply)

37. What steps are typically involved in troubleshooting query performance issues in Snowflake? (Select all that apply)

38. When working with Snowsight dashboards to summarize large data sets, what key advantage do they offer in exploratory analyses?

39. How do exploratory ad-hoc analyses differ from routine analysis?

40. When maintaining reports and dashboards, why is it crucial to configure subscriptions and updates?

41. What actions are typically involved in working with and querying data in Snowflake? (Select all that apply)

42. How do table functions differ from other Snowflake functions?

43. How do row access policies and Dynamic Data Masking impact the creation of dashboards in terms of data visibility and security?

44. How do row access policies and Dynamic Data Masking affect the creation and maintenance of reports and dashboards?

45. When selecting and implementing an effective data model, what considerations are crucial for ensuring its suitability for BI requirements? (Select all that apply)

46. What considerations are essential when identifying the volume of data to be collected in a collection system? (Select all that apply)

47. What is the primary benefit of using User-Defined Functions (UDFs) in SQL for data analysis?

48. When working with semi-structured data in Snowflake, how do built-in functions for traversing, flattening, and nesting aid in data manipulation?

49. How does operationalizing data contribute to maintaining reports and dashboards for business requirements?

50. How do logging and monitoring solutions contribute to data processing solutions? (Select all that apply)

51. When designing a data collection system, what factors should be considered when assessing how often data needs to be collected? (Select all that apply)

52. How do diverse chart types (e.g., bar charts, scatter plots, heat grids) contribute to effective data presentation and visualization in reports and dashboards?

53. What types of Snowflake functions are available for data analysis and manipulation? (Select all that apply)

54. Which action aids in performing a diagnostic analysis on historical data to identify reasons/causes of anomalies?

55. Why are Stored Procedures valuable in data analysis using SQL?

56. How does the utilization of Regular views differ from Materialized views in data analysis?

57. What is the primary benefit of connecting BI tools to Snowflake for dashboard creation?

58. How do Stored Procedures contribute to the efficiency of data analysis using SQL?

59. How does understanding and analyzing the query execution plan contribute to query optimization in Snowflake?

60. How can automated and repeatable tasks contribute to maintaining reports and dashboards in meeting business requirements?

61. How does enriching data through Snowflake Marketplace benefit data analysis? (Select all that apply)

62. What distinguishes Materialized views from Secure views in the context of data analysis?

63. What attributes of the Query Profile are typically assessed to understand query performance in Snowflake?

64. Which considerations are part of best practice for ensuring data integrity structures in Snowflake? (Select all that apply)

65. When customizing data presentations in dashboards using filtering and editing techniques, what advantages do these methods offer? (Select all that apply)

66. How do materialized views differ from regular views in the context of data analysis?

67. In Snowflake, how do window functions differ from table functions?

68. When evaluating and selecting data for building dashboards, what factors should be considered for ensuring data relevance and usefulness? (Select all that apply)

69. In Snowflake, what factors determine the effectiveness of using materialized views for query optimization?

70. Which statement accurately describes the use of regular views in data analysis?

71. What factors should be considered when evaluating which transformations are required in data discovery? (Select all that apply)

72. How do materialized views differ from secure views in data analysis?

73. Which action is essential in performing exploratory ad-hoc analyses?

74. In performing data discovery to identify necessary elements from available datasets, what role do metadata play in this process?

75. When maintaining reports and dashboards, why is it essential to configure subscriptions and updates?