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| Section | Weight | Objectives |
|---|---|---|
| Prepare and Present Data | 10–15% | - Snowsight dashboards and sharing results - Align outputs with business requirements - Data visualization and reporting |
| Use Built-in Functions and Create UDFs | 10–15% | - Scalar, aggregate, table, system functions - User-Defined Functions (UDFs) |
| Prepare and Load Data | 15–20% | - External tables and data validation - File formats: CSV, JSON, Parquet, Avro - Data ingestion methods: COPY INTO, stages, Snowpipe |
| Perform Descriptive and Diagnostic Analysis | 10–15% | - Exploratory and ad-hoc analysis - Statistical summarization and trend analysis - Anomaly detection and root cause analysis |
| Build and Troubleshoot Advanced SQL Queries | 20–25% | - Semi-structured data processing - Complex joins, subqueries, window functions - Query optimization and troubleshooting |
| Perform Predictive Analysis | 5–10% | - Using Snowflake ML and built-in analytics - Forecasting and predictive modeling |
| Perform Simple Data Transformations for Analysis | 15–20% | - Data cleansing, standardization, type conversion - Views, materialized views, CTEs - Handling NULLs and structuring datasets |
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NEW QUESTION # 46
The following code is run:
Then this statement is executed:
What will be the output of this statement?
Answer: B
Explanation:
To determine the correct output, a Data Analyst must understand the behavior of the ILIKE operator, wildcard characters, and the ESCAPE clause in Snowflake.
1. Pattern Matching with ILIKE: The ILIKE operator performs case-insensitive pattern matching. The provided pattern is 'p%
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