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Snowflake DAA-C01 Exam Syllabus Topics:

Section	Weight	Objectives
Data Transformation and Data Modeling	22%-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 Analysis	30%-32%	- Perform advanced analytics using SQL 1. Snowflake-specific analytical features 2. Aggregate functions 3. Time-series analysis
Data Presentation and Data Visualization	28%-29%	- Integrate with BI tools 1. Power BI integration 2. Tableau integration 3. Other partner visualization tools - Create dashboards 1. Present analytical results 2. Snowsight dashboards
Data Ingestion and Data Preparation	15%-20%	- Implement data processing solutions 1. Automate and implement data pipelines (scheduling) 2. Respond to processing failures 3. Use logging and monitoring solutions (auditing, data lineage) 4. Cleanse, conform, and enrich data - Perform data discovery to identify what is needed from available datasets 1. Evaluate required transformations (table joins, set operations, ASOF JOINS) 2. Use commands to read metadata or alter context (DESCRIBE, SHOW, USE) 3. Query tables to assess data elements and statistics maintained by Snowflake 4. Determine the level of data granularity required 5. Identify elements required for business goals using BI reports or SQL analysis - 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) - Enrich data by identifying and accessing relevant data from the Snowflake Marketplace 1. Find external data sets that correlate with available data 2. Create tables and views 3. Use Secure Data Sharing (Marketplace, Internal Marketplace, Private Listings, Listings) - 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 - Prepare data and load into Snowflake 1. Load data from external/internal stages into a table 2. Load files using Snowsight

Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:

Question 1

Which Snowflake feature or object can be used to dynamically create and execute SQL statements?

A. System-defined functions
B. Tasks
C. Stored procedures
D. User-Defined Functions (UDFs)

Question 2

While loading data into Snowflake using named file formats, a file format defined in which location has precedence?

A. The table definition
B. The COPY INTO statement
C. The stage definition
D. The schema definition

Question 3

What is a benefit of using SQL queries that contain secure views?

A. Users will not be able to make observations about the quantity of underlying data.
B. The amount of data scanned, and the total data volume are obfuscated.
C. Snowflake secure views are more performant than regular views.
D. Only the number of scanned micro-partitions is exposed, not the number of bytes scanned.

Question 4

What option would allow a Data Analyst to efficiently estimate cardinality on a data set that contains trillions of rows?

A. Count(Distinct *)/Count(*)
B. SYSTEM$ESTIMATE
C. Count(Distinct *)
D. HLL(*)

Question 5

Which Snowflake feature allows users to encapsulate a series of SQL statements into a reusable database object, facilitating modular code development?

A. Stored procedure
B. Common Table Expressions (CTE)
C. Materialized view
D. User-Defined Function (UDF)

Solutions:

Question 1
Answer: C

Question 2
Answer: B

Question 3
Answer: A

Question 4
Answer: D

Question 5
Answer: A