DAA-C01 Exam Actual Tests - Exam DAA-C01 Introduction

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| Section | Weight | Objectives |
|---|
| Data Presentation and Data Visualization | 28%-29% | - Integrate with BI tools
- 1. Other partner visualization tools
- 2. Tableau integration
- 3. Power BI integration
- Create dashboards
- 1. Present analytical results
- 2. Snowsight dashboards
|
| Data Ingestion and Data Preparation | 15%-20% | - Prepare data and load into Snowflake
- 1. Load data from external/internal stages into a table
- 2. Load files using Snowsight
- Perform data discovery to identify what is needed from available datasets
- 1. Query tables to assess data elements and statistics maintained by Snowflake
- 2. Determine the level of data granularity required
- 3. Identify elements required for business goals using BI reports or SQL analysis
- 4. Evaluate required transformations (table joins, set operations, ASOF JOINS)
- 5. Use commands to read metadata or alter context (DESCRIBE, SHOW, USE)
- Use best practice considerations relating to data integrity structures
- 1. Define primary keys for tables
- 2. Implement constraints
- 3. Perform table joins between parent/child tables
- 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 structured sources (CSV)
- 2. Retrieve data from semi-structured sources (Parquet, Avro, ORC, JSON, XML)
- 3. Synthetic Data Generation
- 4. Retrieve data from unstructured sources
- Implement data processing solutions
- 1. Respond to processing failures
- 2. Use logging and monitoring solutions (auditing, data lineage)
- 3. Automate and implement data pipelines (scheduling)
- 4. Cleanse, conform, and enrich data
|
| Data Transformation and Data Modeling | 22%-30% | - Transform data using SQL
- 1. PIVOT/UNPIVOT operations
- 2. Window functions
- 3. Common Table Expressions (CTEs)
- 4. QUALIFY clauses
- Design data models
- 1. Snowflake schema design
- 2. Star schema design
- 3. Data vault models
|
| Data Analysis | 30%-32% | - Perform advanced analytics using SQL
- 1. Time-series analysis
- 2. Aggregate functions
- 3. Snowflake-specific analytical features
|
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Exam DAA-C01 Introduction - Free DAA-C01 Practice
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Snowflake SnowPro Advanced: Data Analyst Certification Exam Sample Questions (Q17-Q22):
NEW QUESTION # 17
In data presentations for business use analyses, what significance do identifying patterns and trends hold?
- A. Patterns and trends don't impact business use analyses significantly.
- B. Recognizing patterns and trends limits data exploration.
- C. Identifying patterns and trends aids in insightful analyses.
- D. It complicates data analysis, hindering decision-making.
Answer: C
Explanation:
Identifying patterns and trends aids in insightful analyses in business use scenarios.
NEW QUESTION # 18
What considerations are crucial when performing table joins between parent/child tables for maintaining data integrity? (Select all that apply)
- A. Ensuring referential integrity
- B. Establishing foreign key constraints
- C. Matching data types
- D. Data redundancy prevention
Answer: A,B,C
Explanation:
Table joins require considerations such as matching data types, establishing foreign key constraints, and ensuring referential integrity for data integrity maintenance.
NEW QUESTION # 19
An e-commerce company suspects that website performance issues (slow loading times) are negatively impacting conversion rates, particularly for mobile users in specific geographic regions. You have access to the following Snowflake tables: 'WEB SESSIONS' 'session_id', , 'device_type', 'location' , , 'session_start_time' 'TRANSACTIONS': 'transaction_id' , 'session_id', Which SQL query is the MOST appropriate for quantifying the relationship between page load time and conversion rate, specifically for mobile users in the 'California' location?

- A. Option E
- B. Option C
- C. Option B
- D. Option D
- E. Option A
Answer: B
Explanation:
Option C is the most appropriate. It groups page load times into bins (using 'NTILE), allowing you to see how conversion rate changes across different ranges of page load times. This is much more informative than a single average (Option A). Option B provides the conversion rate for each distinct , which is likely to be very granular and difficult to interpret. Option D calculates the correlation coefficient, which is useful but doesn't provide the detailed view of conversion rate across different page load time ranges offered by option C. Option E just groups the time based on User ld, which is useless.
NEW QUESTION # 20
A data analyst needs to perform an exploratory ad-hoc analysis on a large customer order dataset in Snowflake to identify potential fraud. The dataset contains sensitive Personally Identifiable Information (PII). Which of the following approaches BEST balances the need for ad-hoc analysis with data security and compliance?
- A. Create a clone of the production database and grant the analyst full access to the clone.
- B. Mask the PII columns using SnoMlake's Dynamic Data Masking feature in the production environment and grant the analyst access to the production database.
- C. Use Snowflake's data sharing capabilities to share a subset of the production data with the analyst, applying row-level security to filter out sensitive data.
- D. Grant the analyst direct access to the production database with no restrictions, relying on the analyst's ethical responsibility.
- E. Export a sample of the data to a local environment, removing all PII, and provide the sample to the analyst.
Answer: B
Explanation:
Dynamic Data Masking allows the analyst to perform ad-hoc analysis on the production data without exposing sensitive PII. Cloning with full access is risky. Exporting a sample may not be representative. Unrestricted access is a security violation. Data sharing with row-level security can be complex and might still inadvertently expose data.
NEW QUESTION # 21
When maintaining reports and dashboards, why is it crucial to configure subscriptions and updates?
- A. Subscriptions and updates ensure timely information delivery.
- B. They complicate dashboard management without any added benefits.
- C. Configuring these features hampers dashboard usability.
- D. They limit data accessibility for effective dashboard usage.
Answer: A
Explanation:
Subscriptions and updates ensure timely information delivery, a crucial aspect of maintaining reports and dashboards.
NEW QUESTION # 22
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