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Snowflake SnowPro Advanced: Data Analyst Certification Exam Sample Questions (Q148-Q153):
NEW QUESTION # 148
When performing a diagnostic analysis, which actions aid in collecting related data to identify anomalies? (Select all that apply)
- A. Focusing solely on recent data for insights
- B. Analyzing data in isolation
- C. Ignoring statistical trends for focused analysis
- D. Collecting data from various sources
Answer: D
Explanation:
Collecting data from various sources aids in comprehensive analysis, assisting in identifying anomalies.
NEW QUESTION # 149
You are tasked with identifying potential data sources for a new marketing analytics dashboard. The dashboard needs to provide insights into customer behavior across various touchpoints. Which of the following would be the MOST appropriate data sources to consider?
- A. IoT sensor data containing temperature readings.
- B. Salesforce data containing customer interactions and sales opportunities.
- C. Social media activity data ingested via a third-party API and stored in a relational database.
- D. Website clickstream data stored in AWS S3 buckets in Parquet format.
- E. Database containing HR employee data.
Answer: B,C,D
Explanation:
Options A, B, and C are the most relevant data sources for a marketing analytics dashboard focused on customer behavior. Website clickstream data (A) provides insights into user interactions on the website. Social media activity data (B) offers insights into customer sentiment and engagement. Salesforce data (C) provides information about customer interactions and sales opportunities. HR employee data (D) and IoT sensor data (E) are less relevant to customer behavior and marketing analytics.
NEW QUESTION # 150
You are analyzing website traffic data in Snowflake using Snowsight. The data is stored in a table 'WEB TRAFFIC' with columns 'VISIT DATE (DATE), 'PAGE URL' (VARCHAR), 'VISITOR_ID (VARCHAR), and (INT - in seconds). You need to create a Snowsight dashboard to answer the following questions: 1. What is the average session duration per page URL? 2. What is the distribution of session durations (histogram)? 3. How many unique visitors are there per day? Which of the following approaches is the MOST efficient and appropriate for creating this Snowsight dashboard?
- A. Use the Snowsight Notebook feature with Python to load the data into pandas DataFrames. Then, calculate the required aggregations (average session duration, histogram bins, unique visitor counts) using pandas. Finally, create visualization tiles in Snowsight referencing the pandas DataFrames.
- B. Create a single tile in Snowsight using a combination chart. Use the average session duration as the primary series, the histogram as a secondary series plotted on a different axis, and the number of unique visitors as a data label on each data point.
- C. Create three separate tiles in Snowsight, each using a direct SQL query. For the histogram, use the 'WIDTH BUCKET function within the SQL query to categorize session durations into buckets and then visualize the counts.
- D. Create three views on top of the WEB TRAFFIC table. Each view will calculate one of the required metrics. Create three tiles in Snowsight, each querying the corresponding view.
- E. Create a single tile with three tabs. Each tab displays one of the required visualizations (average session duration, histogram, unique visitors). Use the same base SQL query for all three tabs, filtering and aggregating the data differently for each tab.
Answer: C
Explanation:
Option A is the most efficient and appropriate. Snowsight's direct SQL query functionality, coupled with the 'WIDTH_BUCKET' function, provides a straightforward and performant way to create the required visualizations. Using views (Option E) adds an unnecessary layer of abstraction. Trying to combine all visualizations into a single tile (Options B and D) is not suitable for the different visualization types. Using Snowsight Notebook (Option C) introduces unnecessary overhead for this relatively simple descriptive analysis task. While Notebooks are powerful, they're best used for more complex data transformations and analysis that SQL cannot easily handle.
NEW QUESTION # 151
Identifying demographics and relationships in a dataset is crucial for:
- A. Error handling
- B. Database normalization
- C. Data cleaning
- D. Data modeling
Answer: D
NEW QUESTION # 152
What is the primary purpose of implementing data processing solutions?
- A. Simplify data access for users
- B. Limit data processing to batch operations
- C. Respond effectively to processing failures
- D. Automate data analysis entirely
Answer: C
Explanation:
Data processing solutions help respond effectively to processing failures for uninterrupted operations.
NEW QUESTION # 153
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