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Snowflake DAA-C01 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Perform Descriptive and Diagnostic Analysis | 10–15% | - Exploratory and ad-hoc analysis - Statistical summarization and trend analysis - Anomaly detection and root cause analysis |
| Topic 2: Use Built-in Functions and Create UDFs | 10–15% | - Scalar, aggregate, table, system functions - User-Defined Functions (UDFs) |
| Topic 3: Build and Troubleshoot Advanced SQL Queries | 20–25% | - Query optimization and troubleshooting - Semi-structured data processing - Complex joins, subqueries, window functions |
| Topic 4: Perform Predictive Analysis | 5–10% | - Forecasting and predictive modeling - Using Snowflake ML and built-in analytics |
| Topic 5: Prepare and Present Data | 10–15% | - Align outputs with business requirements - Data visualization and reporting - Snowsight dashboards and sharing results |
| Topic 6: Prepare and Load Data | 15–20% | - External tables and data validation - Data ingestion methods: COPY INTO, stages, Snowpipe - File formats: CSV, JSON, Parquet, Avro |
| Topic 7: Perform Simple Data Transformations for Analysis | 15–20% | - Data cleansing, standardization, type conversion - Handling NULLs and structuring datasets - Views, materialized views, CTEs |
Snowflake SnowPro Advanced: Data Analyst Certification Sample Questions:
1. What will the following query return?
SELECT * FROM testtable SAMPLE BLOCK (0.012) REPEATABLE (99992);
A) A sample of a table in which each block of rows has a 1.2% probability of being included in the sample where repeated elements are allowed.
B) A sample containing 99992 records of a table in which each block of rows has a 0.012% probability of being included in the sample.
C) A sample of a table in which each block of rows has a 1.2% probability of being included in the sample, with the seed set to 99992.
D) A sample of a table in which each block of rows has a 0.012% probability of being included in the sample, with the seed set to 99992.
2. A Data Analyst executes a complex query. Which query will allow the Analyst to access the results a second time?
A) DESC RESULT LAST_QUERY_ID();
B) SELECT * FROM TABLE(RESULT_SCAN(LAST_QUERY_ID()));
C) SELECT * FROM TABLE(INFORMATION_SCHEMA.QUERY_HISTORY());
D) SELECT LAST_QUERY_ID(-1);
3. What does the "SQL keyword" refer to in the context of adding filters to a worksheet?
A) The name of a User-Defined Function (UDF) used to define the filter "key" values
B) The filter name to be inserted into queries
C) The table name containing the static filter "key" values
D) The name of the function used to generate the filter
4. A Data Analyst needs to add address details based on a customer's latitude and longitude to a customer sales database. The Analyst found a free Worldwide Address Data listing on the Snowflake Marketplace. The ACCOUNTADMIN placed the data set into a new database called ADDRESS_DATA. The Data Analyst needs to join the ADDRESS_DATA.OPENADDRESS table with the ORDERS table which is stored in the GLOBAL_DWH database. The combined data set needs to be created as a view. How can this be achieved?
A) Create a view in the ADDRESS_DATA database.
B) Create a view in the GLOBAL_DWH database.
C) Create a new schema called ENRICHED in the ADDRESS_DATA database and create this view in the ENRICHED schema.
D) Ask the ACCOUNTADMIN to grant the Data Analyst the IMPORTED_PRIVILEGES on the ADDRESS_DATA database and then create a view in the ADDRESS_DATA database.
5. Why would an INFER_SCHEMA table function be used?
A) To retrieve the column definitions from a previously-loaded database table
B) To detect the metadata schema from a table cell that contains JSON data
C) To detect the file metadata schema from staged data files that contain unstructured data
D) To detect the file metadata schema from staged data files that contain semi-structured data
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: B | Question # 3 Answer: B | Question # 4 Answer: B | Question # 5 Answer: D |
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