Snowflake DAA-C01 Certification Exam Sample Questions

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Snowflake DAA-C01 Sample Questions:

01. When planning for data volume collection, what is an important consideration to ensure scalability and performance?
a) The physical location of data
b) The types of data visualization tools used
c) The data processing capabilities
d) The expected growth rate of data
 
02. Configuring subscriptions and updates in a dashboard tool primarily helps in:
a) Changing the dashboard layout
b) Reducing the size of the data
c) Ensuring users receive the latest data
d) Enhancing the security of the data
 
03. What is a critical consideration when using data shares in Snowflake to join data with existing datasets?
a) Ensuring data schema compatibility
b) The number of likes on the Snowflake’s social media page
c) The visual appeal of the data
d) The brand of the data visualization tool
 
04. A key aspect of performing exploratory ad-hoc analyses is:
a) Following a strict data model
b) Relying solely on predefined hypotheses
c) Flexibility in querying and data exploration
d) Limiting data sources
 
05. Which approach is most suitable for making data-driven predictions?
a) Basic SQL queries
b) Using built-in SQL functions for statistical analysis
c) Relying on external data sources only
d) Ignoring historical data trends
 
06. Why is the Parquet format preferred for complex data sets?
a) It has visually appealing data presentation
b) It supports efficient compression and encoding schemes
c) It randomly alters data for testing
d) It changes data colors for differentiation
 
07. Data clustering is an example of which type of data analysis technique?
a) Descriptive analysis
b) Predictive analysis
c) Prescriptive analysis
d) Exploratory analysis
 
08. What are important factors to consider when creating tables and views in Snowflake?
(Choose three)
a) Data security and access controls
b) The color of the tables and views
c) Optimization for query performance
d) Documentation and metadata management
 
09. Which of the following is a key step in data preparation?
a) Data normalization
b) Model deployment
c) Algorithm selection
d) Visual analysis
 
10. Identifying demographics and relationships in a dataset is crucial for:
a) Data cleaning
b) Error handling
c) Data modeling
d) Database normalization

Answers:

Question: 01
Answer: d		 Question: 02
Answer: c		 Question: 03
Answer: a		 Question: 04
Answer: c		 Question: 05
Answer: b
Question: 06
Answer: b		 Question: 07
Answer: a		 Question: 08
Answer: a, c, d		 Question: 09
Answer: a		 Question: 10
Answer: c

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