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Snowflake DAA-C01 Exam Syllabus Topics:

SectionWeightObjectives
Data Transformation and Data Modeling22%-30%- Transform data using SQL
  • 1. Window functions
  • 2. QUALIFY clauses
  • 3. PIVOT/UNPIVOT operations
  • 4. Common Table Expressions (CTEs)
- Design data models
  • 1. Data vault models
  • 2. Star schema design
  • 3. Snowflake schema design
Data Ingestion and Data Preparation15%-20%- 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. Determine the level of data granularity required
  • 3. Evaluate required transformations (table joins, set operations, ASOF JOINS)
  • 4. Use commands to read metadata or alter context (DESCRIBE, SHOW, USE)
  • 5. Query tables to assess data elements and statistics maintained by Snowflake
- 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
- Enrich data by identifying and accessing relevant data from the Snowflake Marketplace
  • 1. Create tables and views
  • 2. Use Secure Data Sharing (Marketplace, Internal Marketplace, Private Listings, Listings)
  • 3. Find external data sets that correlate with available data
- Implement data processing solutions
  • 1. Cleanse, conform, and enrich data
  • 2. Automate and implement data pipelines (scheduling)
  • 3. Respond to processing failures
  • 4. Use logging and monitoring solutions (auditing, data lineage)
- Prepare data and load into Snowflake
  • 1. Load files using Snowsight
  • 2. Load data from external/internal stages into a table
- Use a collection system to retrieve data
  • 1. Retrieve data from semi-structured sources (Parquet, Avro, ORC, JSON, XML)
  • 2. Synthetic Data Generation
  • 3. Retrieve data from structured sources (CSV)
  • 4. Retrieve data from unstructured sources
Data Analysis30%-32%- Perform advanced analytics using SQL
  • 1. Snowflake-specific analytical features
  • 2. Time-series analysis
  • 3. Aggregate functions
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

Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:

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

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


2. The image shows a table with a variant column that is storing a JSON record:

This SQL query is run:

What will be the result?

A)

B)

C)

D)


3. A Data Analyst has been analyzing customer data in several worksheets. Each worksheet contains a complex query that provides clean and prepared data for visualizations. The Analyst has also created a Customer Overview dashboard in Snowsight. How should the Analyst add the worksheets in the Customer Analysis database to the dashboard, using the LEAST amount of operational overhead?

A) Open each worksheet, copy the query, then paste the query into the dashboard.
B) Move the worksheets into the dashboard.
C) Copy and paste the worksheets into the dashboard.
D) Query the QUERY_HISTORY view to find those queries, then add the queries into the dashboard.


4. A Data Analyst created a cost overview dashboard in Snowsight. Management has asked for a system date filter to easily change the time period and refresh the data in all dashboard tiles with a single filter selection.
The system date filter is shown below:

The Analyst wants to apply the filter onto individual dashboard components.
Adding which where clause to the queries will apply the filter as required?

A) Where start_time = :daterange
B) Where start_time >= dateadd('days', -7, CURRENT_TIMESTAMP())
C) Where start_time >= dateadd('days', -7, SYSDATE())
D) Where start_time = :date_filter


5. A Data Analyst runs a query in a Snowflake worksheet, and selects a numeric column from the result grid.
What automatically-generated contextual statistic can be visualized?

A) A frequency distribution, displayed for all numeric columns
B) A histogram, displayed for all numeric, date, and time columns
C) MIN/MAX values for the column
D) A key distribution


Solutions:

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

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