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Snowflake DAA-C01 Exam Syllabus Topics:

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

Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:

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

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


2. There are two similarly-structured and sized tables, Table_a and Table_b, in a schema with data populated in both tables. A Data Analyst is running queries as part of a preliminary analysis of the data to check the MAX value of a numeric column named num which is present in both the tables:
* Query 1: SELECT MAX(num) FROM Table_a;
* Query 2: SELECT MAX(num) FROM Table_b;
After running the queries, the Analyst observed that Query 2 ran significantly slower than Query 1. Why is this occurring?

A) The USE_CACHED_RESULT was set to FALSE before running Query 2.
B) Table_b has more rows than Table_a.
C) Table_b has a row-access policy defined.
D) A multi-cluster warehouse was used to run Query 1.


3. The following code is run:

Then this statement is executed:

What will be the output of this statement?

A)

B)

C)

D)


4. Which query will provide this data without incurring additional storage costs?

A) CREATE TABLE DEV.PUBLIC.TRANS_HIST CLONE PROD.PUBLIC.TRANS_HIST;
B) CREATE TABLE DEV.PUBLIC.TRANS_HIST AS (SELECT * FROM PROD.PUBLIC.TRANS_HIST WHERE extract(year from (TRANS_DATE)) = 2019);
C) CREATE TABLE DEV.PUBLIC.TRANS_HIST AS (SELECT * FROM PROD.PUBLIC.
TRANS_HIST);
D) CREATE TABLE DEV.PUBLIC.TRANS_HIST LIKE PROD.PUBLIC.TRANS_HIST;


5. A Data Analyst has a Parquet file stored in an Amazon S3 staging area. Which query will copy the data from the staged Parquet file into separate columns in the target table?

A) Option D
B) Option A
C) Option C
D) Option B


Solutions:

Question # 1
Answer: D
Question # 2
Answer: C
Question # 3
Answer: A
Question # 4
Answer: A
Question # 5
Answer: C

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