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Snowflake DAA-C01 Exam Syllabus Topics:

SectionWeightObjectives
Data Transformation and Data Modeling22%-30%- Transform data using SQL
  • 1. PIVOT/UNPIVOT operations
  • 2. Common Table Expressions (CTEs)
  • 3. Window functions
  • 4. QUALIFY clauses
- Design data models
  • 1. Snowflake schema design
  • 2. Data vault models
  • 3. Star schema design
Data Ingestion and Data Preparation15%-20%- Enrich data by identifying and accessing relevant data from the Snowflake Marketplace
  • 1. Use Secure Data Sharing (Marketplace, Internal Marketplace, Private Listings, Listings)
  • 2. Create tables and views
  • 3. Find external data sets that correlate with available data
- Use best practice considerations relating to data integrity structures
  • 1. Define primary keys for tables
  • 2. Perform table joins between parent/child tables
  • 3. Implement constraints
- Implement data processing solutions
  • 1. Respond to processing failures
  • 2. Automate and implement data pipelines (scheduling)
  • 3. Cleanse, conform, and enrich data
  • 4. Use logging and monitoring solutions (auditing, data lineage)
- Prepare data and load into Snowflake
  • 1. Load data from external/internal stages into a table
  • 2. Load files using Snowsight
- Use a collection system to retrieve data
  • 1. Synthetic Data Generation
  • 2. Retrieve data from unstructured sources
  • 3. Retrieve data from structured sources (CSV)
  • 4. Retrieve data from semi-structured sources (Parquet, Avro, ORC, JSON, XML)
- Perform data discovery to identify what is needed from available datasets
  • 1. Identify elements required for business goals using BI reports or SQL analysis
  • 2. Evaluate required transformations (table joins, set operations, ASOF JOINS)
  • 3. Determine the level of data granularity required
  • 4. Query tables to assess data elements and statistics maintained by Snowflake
  • 5. Use commands to read metadata or alter context (DESCRIBE, SHOW, USE)
Data Presentation and Data Visualization28%-29%- Create dashboards
  • 1. Present analytical results
  • 2. Snowsight dashboards
- Integrate with BI tools
  • 1. Tableau integration
  • 2. Other partner visualization tools
  • 3. Power BI integration
Data Analysis30%-32%- Perform advanced analytics using SQL
  • 1. Snowflake-specific analytical features
  • 2. Time-series analysis
  • 3. Aggregate functions

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Snowflake SnowPro Advanced: Data Analyst Certification Exam Sample Questions (Q33-Q38):

NEW QUESTION # 33
When utilizing materialized views, what benefit do they offer in terms of query performance and data retrieval?

Answer: C

Explanation:
Materialized views provide precomputed snapshots, enhancing query performance.


NEW QUESTION # 34
You have a table named 'ORDERS with a 'ORDER DATE column stored as VARCHAR. The column contains dates in the format 'YYYY-MM-DD HH24:Ml:SS.FF3'. You need to calculate the number of orders placed in January 2023. Which of the following SQL statements will achieve this most efficiently and accurately, considering potential time zone differences configured at the user or account level?

Answer: D

Explanation:
Option E is the most robust because it explicitly handles the VARCHAR to TIMESTAMP conversion, incorporates timezone conversion from UTC to the session's timezone, and then extracts the DATE part for accurate filtering. This accounts for potential timezone discrepancies that might affect date boundaries. Options A and B rely on string manipulation, which is prone to errors and not recommended for date operations. Option C lacks time zone considerations, which can lead to issues. Option D is less efficient because MONTH() and YEAR() function needs to be applied, and it also lacks timezone conversion consideration.


NEW QUESTION # 35
When evaluating and selecting data for building dashboards, what factors should be considered for ensuring data relevance and usefulness? (Select all that apply)

Answer: A,D

Explanation:
To ensure relevant and useful dashboards, data must be evaluated based on business requirements and filtered for irrelevant attributes.


NEW QUESTION # 36
How do Snowsight's data loading capabilities impact data ingestion?

Answer: A

Explanation:
Snowsight allows streamlined data import from various sources, enhancing data ingestion capabilities.


NEW QUESTION # 37
When automating and repeating data processing tasks, what challenges might be encountered in managing and sharing Snowsight dashboards effectively?

Answer: B,D

Explanation:
Managing Snowsight dashboards might pose challenges related to limited user access control and embedding external content seamlessly within the dashboards.


NEW QUESTION # 38
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