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

Account and Security - 25-30%
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.
  • Parameters (all levels)
    - Account parameters
    - Object parameters
  • Outline the Snowflake parameter hierarchy and the relationship between the parameter types.

- List the benefits and limitations of one Snowflake account as compared to multiple Snowflake accounts.

  • Isolate or segment accounts
  • Key considerations and constraints when defining an account strategy
  • Features/capabilities that can be leveraged across accounts
  • Identify use cases that are appropriate for account strategies
Design an architecture that meets data security, privacy, compliance, and governance requirements. - Configure Role Based Access Control (RBAC) hierarchy
  • Privilege inheritance
  • Database roles
  • System roles and associated best practices
  • Functional roles compared to access roles

- Data Access

  • Storage integrations

- Data Security

  • Secure views
  • Column-level security
    - Dynamic Data Masking
    - Row level security
    - Row access policies
  • Compliance
  • Payment Card Industry (PCI) Security Standard
  • Personal Identifiable Information (PII)/ Personal Health Information (PHI)
  • Features of the different Snowflake editions
Outline Snowflake security principles and identify use cases where they should be applied. - Encryption
- Network security
  • Access control lists
  • AWS PrivateLink/Azure Private Link

- User, role, grants provisioning
- Authentication

  • Federated authentication
  • Single Sign-on (SSO)
  • Multi-Factor Authentication (MFA)
  • Key-pair authentication
  • Security integrations

Snowflake Architecture - 25-30%
Outline the benefits and limitations of various data models in a Snowflake environment. - Data models
- Use of key/column constraints (ENABLE/RELY/VALIDATE)
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

- Snowflake Marketplace
- Data Exchange
- Data sharing methods

  • Configure shares, account parameters, and privileges
  • Security patterns for data sharing
  • Outline the purpose, benefits, and capabilities of the multiple data sharing methods
Create architecture solutions that support development lifecycles as well as workload requirements. - Data lake and environments
  • Storage directory structure
  • Zones (data warehouse layers)
  • Support of DevOps/DataOps principles
  • Production/development/sandbox
  • Data workloads
  • Data warehouse
  • ELT/ETL

- Development lifecycle support

  • Migration
    - CI/CD
  • Deployment
  • Rollback process
Given a scenario, outline how objects exist within the Snowflake object hierarchy and how the hierarchy impacts an architecture. - Roles
- Virtual warehouses
- Object hierarchy
  • Databases
    - CI/CD

- Tables
- Views
- Stages
- File formats
- Functions
- Procedures
- Streams and tasks
Determine the appropriate data recovery solution in Snowflake and how data can be restored. - Backup/recovery
  • Time Travel
    - Table types
    - Costs
    - Availability
    - Query performance impacts
  • Data corruption impacts
  • Fail-safe

- Disaster recovery

  • Replication and failover
  • Zero-copy cloning

Data Engineering - 20-25%
Determine the appropriate data loading or data unloading solution to meet business needs. - Data sources
  • Data at rest
  • Data in motion
  • External sources and formats
  • Streaming data
    - Snowpipe
    - Change Data Capture (CDC)
  • OLTP/RDBMS sources
  • API sources

- Data ingestion

  • Bulk file upload
  • Snowpipe
  • External tables
  • Reload process
  • Incremental updates compared to full updates
  • Iceberg tables
  • Parameters for copying data and addressing data handling error

- Architecture changes

  • Schema detection and table schema evolution
  • Data source changes

- Data unloading
Outline key tools in Snowflake’s ecosystem and how they interact with Snowflake. - Connectors
  • Kafka
  • Spark
  • Python

- Drivers

  • JDBC
  • ODBC

- API endpoints

  • Use of system$allowlist

- SnowSQL
- Snowpark

  • Python
  • Scala
  • Java
Determine the appropriate data transformation solution to meet business needs.

- Views and tables

  • Benefits, limitations, properties
  • Relationship and impact between the view and data types
  • Impact of costs
  • Dynamic tables

- Staging layers and tables
- Querying semi-structured data

  • Flattened

- Data processing
- Stored procedures
- Streams and tasks
- Functions

  • External functions
    - Performance impacts
  • User-Defined Functions (UDFs)
  • User-Defined Table Functions (UDTFs)
  • Secure functions

Performance Optimization - 20-25%
Outline performance tools, best practices, and appropriate scenarios where they should be applied. - Query profiling
  • Interpret a Query Profile, identify bottlenecks, and outline recommendations
  • Metadata functions

- Virtual warehouse configurations

  • Auto-suspend/resume
  • Scale up/down (resizing)
  • Scale in/out (multi-cluster warehouse/auto-scaling)
  • Query acceleration service
  • Warehouse queuing
  • Snowpark-optimized warehouses

- Clustering

  • Natural clustering
  • Auto-clustering
  • Clustering keys

- Search optimization service
- Caching

  • Different cache layers
  • Cache expiration
  • Impact of costs
Troubleshoot performance issues with existing architectures. - Use of system clustering information
- Warehouse configurations
- Optimization techniques
- Micro-partition pruning
- Monitoring and alerting
  • Use of the Account Usage and Information schemas
  • Resource monitoring
  • Email notifications
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