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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prepare and Present Data | 10–15% | - Align outputs with business requirements - Data visualization and reporting - Snowsight dashboards and sharing results |
| Topic 2: Perform Descriptive and Diagnostic Analysis | 10–15% | - Statistical summarization and trend analysis - Anomaly detection and root cause analysis - Exploratory and ad-hoc analysis |
| Topic 3: Prepare and Load Data | 15–20% | - External tables and data validation - File formats: CSV, JSON, Parquet, Avro - Data ingestion methods: COPY INTO, stages, Snowpipe |
| Topic 4: Perform Simple Data Transformations for Analysis | 15–20% | - Views, materialized views, CTEs - Handling NULLs and structuring datasets - Data cleansing, standardization, type conversion |
| Topic 5: Use Built-in Functions and Create UDFs | 10–15% | - User-Defined Functions (UDFs) - Scalar, aggregate, table, system functions |
| Topic 6: Build and Troubleshoot Advanced SQL Queries | 20–25% | - Semi-structured data processing - Complex joins, subqueries, window functions - Query optimization and troubleshooting |
| Topic 7: Perform Predictive Analysis | 5–10% | - Using Snowflake ML and built-in analytics - Forecasting and predictive modeling |
1. A Data Analyst needs to generate a graphic that will identify any natural clusters in a data set containing details about completed orders. Which Snowsight chart should be used?
A) Bar chart
B) Line chart
C) Scatter plot
D) Heat grid
2. A Data Analyst is working with a table that has 1 record per day, with sales information. Which window function would calculate a 7-day moving average of sales, where SALES_DATE represents the date column?
A) AVG(SALES) OVER (ORDER BY SALES_DATE ROWS BETWEEN 7 PRECEDING AND
CURRENT ROW)
B) SUM(SALES) OVER (ORDER BY SALES_DATE ROWS BETWEEN 7 PRECEDING AND
CURRENT ROW)
C) SUM(SALES) OVER (ORDER BY SALES_DATE ROWS BETWEEN 6 PRECEDING AND
CURRENT ROW)
D) AVG(SALES) OVER (ORDER BY SALES_DATE ROWS BETWEEN 6 PRECEDING AND
CURRENT ROW)
3. What will the following query return?
SELECT * FROM testtable SAMPLE BLOCK (0.012) REPEATABLE (99992);
A) 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.
B) 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.
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 1.2% probability of being included in the sample where repeated elements are allowed.
4. 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 B
B) Option D
C) Option C
D) Option A
5. 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 = :date_filter
B) Where start_time = :daterange
C) Where start_time >= dateadd('days', -7, CURRENT_TIMESTAMP())
D) Where start_time >= dateadd('days', -7, SYSDATE())
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: B |
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