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Snowflake DAA-C01 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Ingestion and Data Preparation15%-20%- Use best practice considerations relating to data integrity structures
  • 1. Perform table joins between parent/child tables
  • 2. Define primary keys for tables
  • 3. Implement constraints
- Perform data discovery to identify what is needed from available datasets
  • 1. Query tables to assess data elements and statistics maintained by Snowflake
  • 2. Evaluate required transformations (table joins, set operations, ASOF JOINS)
  • 3. Determine the level of data granularity required
  • 4. Use commands to read metadata or alter context (DESCRIBE, SHOW, USE)
  • 5. Identify elements required for business goals using BI reports or SQL analysis
- Implement data processing solutions
  • 1. Automate and implement data pipelines (scheduling)
  • 2. Use logging and monitoring solutions (auditing, data lineage)
  • 3. Respond to processing failures
  • 4. Cleanse, conform, and enrich data
- Enrich data by identifying and accessing relevant data from the Snowflake Marketplace
  • 1. Find external data sets that correlate with available data
  • 2. Use Secure Data Sharing (Marketplace, Internal Marketplace, Private Listings, Listings)
  • 3. Create tables and views
- Use a collection system to retrieve data
  • 1. Retrieve data from semi-structured sources (Parquet, Avro, ORC, JSON, XML)
  • 2. Synthetic Data Generation
  • 3. Retrieve data from structured sources (CSV)
  • 4. Retrieve data from unstructured sources
- Prepare data and load into Snowflake
  • 1. Load files using Snowsight
  • 2. Load data from external/internal stages into a table
Topic 2: Data Transformation and Data Modeling22%-30%- Transform data using SQL
  • 1. QUALIFY clauses
  • 2. PIVOT/UNPIVOT operations
  • 3. Common Table Expressions (CTEs)
  • 4. Window functions
- Design data models
  • 1. Snowflake schema design
  • 2. Star schema design
  • 3. Data vault models
Topic 3: Data Presentation and Data Visualization28%-29%- Integrate with BI tools
  • 1. Power BI integration
  • 2. Other partner visualization tools
  • 3. Tableau integration
- Create dashboards
  • 1. Snowsight dashboards
  • 2. Present analytical results
Topic 4: Data Analysis30%-32%- Perform advanced analytics using SQL
  • 1. Snowflake-specific analytical features
  • 2. Time-series analysis
  • 3. Aggregate functions

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Quiz Snowflake - Professional DAA-C01 - SnowPro Advanced: Data Analyst Certification Exam Free Test Questions

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Snowflake SnowPro Advanced: Data Analyst Certification Exam Sample Questions (Q27-Q32):

NEW QUESTION # 27
Which Snowflake feature allows users to encapsulate a series of SQL statements into a reusable database object, facilitating modular code development?

Answer: C


NEW QUESTION # 28
When employing different modeling techniques for the consumption layer in Snowflake (e.g., dimensional, Data Vault), what factors influence the choice between these techniques?

Answer: A,B,D

Explanation:
Choosing modeling techniques depends on factors like data transformation complexity, consistency requirements, and preferences for query performance optimization when designing the consumption layer in Snowflake.


NEW QUESTION # 29
A retail company is analyzing sales data to optimize product placement and promotional campaigns. They have sales figures, customer demographics, and promotional campaign details stored in Snowflake. Which visualization technique and Snowflake feature combination would BEST help them identify nuanced correlations between customer age, product category, and the success rate of different promotional campaigns, allowing for interactive exploration and drill-down capabilities?

Answer: B

Explanation:
Option B is the most appropriate because it leverages an interactive dashboard (Streamlit) connected to Snowflake, enabling cross- filtering and drill-down capabilities. Using stored procedures in Snowflake to pre-calculate aggregated data enhances dashboard performance. Option A provides a static view, lacking interactivity. Option C relies on a static table, which is not ideal for exploratory analysis. Option D involves exporting data outside Snowflake, which is inefficient and less secure. Option E might not provide the specific visualizations or level of customization needed for detailed correlation analysis. The use of the heatmap allows a clearer correlation view.


NEW QUESTION # 30
You've created a Snowflake dashboard for your company's sales team using a Bl tool. The dashboard displays real-time sales data pulled directly from Snowflake. The sales team wants to be automatically notified whenever a particular product's sales exceed a certain threshold in a given day. You need to implement a system to accomplish this. Which of the following methods offer a way to trigger notifications based on data changes in Snowflake AND integrate with an external notification system (e.g., Slack, Email)? Select all that apply:

Answer: C,D

Explanation:
A and B offer native Snowflake capabilities for triggering actions based on data conditions and integrating with external systems. Alerts are designed for real-time monitoring and can call external functions to send notifications. Tasks can be scheduled to perform periodic checks and trigger notifications through stored procedures and external APIs. C: Streams and Pipes are primarily for continuous data loading and transformation, not direct notification triggering based on data conditions. It's an indirect method. D: BI tools are not the primary component for handling real time alerting based on exceeding specific values. E: Replication is for disaster recovery/high availability and doesn't address real- time notifications.


NEW QUESTION # 31
You have a table named 'ORDERS with a 'ORDER DATE column stored as VARCHAR. The column contains dates in the format 'YYYY-MM-DD HH24:Ml:SS.FF3'. You need to calculate the number of orders placed in January 2023. Which of the following SQL statements will achieve this most efficiently and accurately, considering potential time zone differences configured at the user or account level?

Answer: D

Explanation:
Option E is the most robust because it explicitly handles the VARCHAR to TIMESTAMP conversion, incorporates timezone conversion from UTC to the session's timezone, and then extracts the DATE part for accurate filtering. This accounts for potential timezone discrepancies that might affect date boundaries. Options A and B rely on string manipulation, which is prone to errors and not recommended for date operations. Option C lacks time zone considerations, which can lead to issues. Option D is less efficient because MONTH() and YEAR() function needs to be applied, and it also lacks timezone conversion consideration.


NEW QUESTION # 32
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The Snowflake DAA-C01 certification is a valuable credential that plays a significant role in advancing the Snowflake professional's career in the tech industry. With the SnowPro Advanced: Data Analyst Certification Exam (DAA-C01) certification exam you can demonstrate your skills and knowledge level and get solid proof of your expertise. You can use this proof to advance your career. The Snowflake DAA-C01 Certification Exam enables you to increase job opportunities, promotes professional development, and higher salary potential, and helps you to gain a competitive edge in your job search.

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