Snowflake SnowPro Advanced - Architect Certification Exam Syllabus

ARA-C01 Dumps Questions, ARA-C01 PDF, SnowPro Advanced - Architect Exam Questions PDF, Snowflake ARA-C01 Dumps Free, SnowPro Advanced - Architect Official Cert Guide PDFThe Snowflake ARA-C01 exam preparation guide is designed to provide candidates with necessary information about the SnowPro Advanced - Architect exam. It includes exam summary, sample questions, practice test, objectives and ways to interpret the exam objectives to enable candidates to assess the types of questions-answers that may be asked during the Snowflake Certified SnowPro Advanced - Architect exam.

It is recommended for all the candidates to refer the ARA-C01 objectives and sample questions provided in this preparation guide. The Snowflake SnowPro Advanced - Architect certification is mainly targeted to the candidates who want to build their career in Advance domain and demonstrate their expertise. We suggest you to use practice exam listed in this cert guide to get used to with exam environment and identify the knowledge areas where you need more work prior to taking the actual Snowflake SnowPro Advanced - Architect exam.

Snowflake ARA-C01 Exam Summary:

Exam Name
Snowflake SnowPro Advanced - Architect
Exam Code ARA-C01
Exam Price $375 USD
Duration 115 minutes
Number of Questions 65
Passing Score 750 + Scaled Scoring from 0 - 1000
Recommended Training / Books Snowflake Advanced Training
SnowPro Advanced: Architect Study Guide
Schedule Exam PEARSON VUE
Sample Questions Snowflake ARA-C01 Sample Questions
Recommended Practice Snowflake Certified SnowPro Advanced - Architect Practice Test

Snowflake SnowPro Advanced - Architect Syllabus:

Section Objectives Weight
Account and Security - Design a Snowflake account and database strategy, based on business requirements.
  • Create and configure Snowflake parameters based on a central account and any additional accounts.
  • List the benefits and limitations of one Snowflake account as compared to multiple Snowflake accounts.
- Design an architecture that meets data security, privacy, compliance, and governance requirements.
  • Configure Role Based Access Control (RBAC) hierarchy
  • System roles and associated best practices
  • Data Access
  • Data Security
  • Compliance
- Outline Snowflake security principles and identify use cases where they should be applied.
  • Encryption
  • Network security
  • User, Role, Grants provisioning
  • Authentication
30%
Snowflake Architecture - Outline the benefits and limitations of various data models in a Snowflake environment.
  • Data models

- Design data sharing solutions, based on different use cases.

  • Use Cases
    - Sharing within the same organization/same Snowflake account
    - Sharing within a cloud region
    - Sharing across cloud regions
    - Sharing between different Snowflake accounts
    - Sharing to a non-Snowflake customer
    - Sharing Across platforms
  • Data Exchange
  • Data Sharing Methods

- Create architecture solutions that support Development Lifecycles as well as workload requirements.

  • Data Lake and Environments
  • Workloads
  • Development lifecycle support

- Given a scenario, outline how objects exist within the Snowflake Object hierarchy and how the hierarchy impacts an architecture.

  • Roles
  • Warehouses
  • Object hierarchy
  • Database

- Determine the appropriate data recovery solution in Snowflake and how data can be restored.

  • Backup/Recovery
  • Disaster Recovery
25%
Data Engineering - Determine the appropriate data loading or data unloading solution to meet business needs.
  • Data sources
  • Ingestion of the data
  • Architecture Changes
  • Data unloading
- Outline key tools in Snowflake’s ecosystem and how they interact with Snowflake.
  • Connectors
    - Kafka
    - Spark
    - Python
  • Drivers
    - JDBC
    - OBDC
    - API endpoints
    - SnowSQL
- Determine the appropriate data transformation solution to meet business needs.
  • Materialized Views, Views and Secure Views
  • Staging layers and tables
  • Querying semi-structured data
  • Data processing
  • Stored Procedures
  • Streams and Tasks
  • Functions
20%
Performance Optimization - Outline performance tools, best practices, and appropriate scenarios where they should be applied.
  • Query profiling
  • Virtual Warehouse configuration
  • Clustering
  • Search Optimization
  • Caching
  • Query rewrite
- Troubleshoot performance issues with existing architectures.
  • JOIN explosions
  • Warehouse selection (scaling up as compared to scaling out)
  • Best practices and optimization techniques
  • Duplication of data
25%
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