Description

SnowPro® Advanced: Architect Overview

The SnowPro® Advanced: Architect Certification will test advanced knowledge and skills used to apply comprehensive architect solutions using Snowflake. This certification will test the ability to:

1. Design an end-to-end data flow from source to consumption using Snowflake’s Platform.
2. Design and deploy a data architecture that meets business, security, and compliance requirements.
3. Select appropriate Snowflake and third-party tools to optimize architecture performance.
4. Design and deploy a shared data set using the Snowflake Marketplace and Data Exchange.

SnowPro® Advanced: Architect Candidate

2+ years of practical experience with Snowflake as an Architect in a production environment. In these two years, successful candidates would have achieved hands-on expertise with SQL and SQL analytics, experience building out a complex ETL/ELT pipeline, experience implementing security and compliance requirements, and working with different data modeling techniques. Having coding experience outside of SQL and DevOps/DataOps design experience is a plus.

Target Audience:

1. Solution Architects
2. Database Architects
3. System Architects

Exam Format:

1. Exam Version: ARA-C01
2. Total Number of Questions: 65
3. Question Types: Multiple Select, Multiple Choice
4. Time Limits: 115 minutes
5. Language: English
6. Registration fee: USD 375
7. Passing Score: 750 + Scaled Scoring from 0 – 1000

Unscored Content:

Exams may include unscored items to gather statistical information for future use. These items are not identified on the form and do not impact your score, and additional time is factored into account for this content.

Prerequisites:

SnowPro Core Certified
Delivery Options:

1. Online Proctoring
2. Onsite Testing Centers

Exam Domain Breakdown:

This exam guide includes test domains, weightings, and objectives. It is not a comprehensive listing of all the content that will be presented in this examination. The table below lists the main content domains and their weightings.

Exam Topics:

Outlined below are the Domains & Objectives measured on the exam. To view subtopics, download the exam study guide.

Accounts and Security

1. Design a Snowflake account and database strategy, based on business requirements.
2. Design an architecture that meets data security, privacy, compliance, and governance requirements.
3. Outline Snowflake security principles and identify use cases where they should be applied.

Snowflake Architecture

1. Outline the benefits and limitations of various data models in a Snowflake environment.
2. Design data sharing solutions, based on different use cases.
3. Create architecture solutions that support Development Lifecycles as well as workload requirements.
4. Given a scenario, outline how objects exist within the Snowflake Object hierarchy and how the hierarchy impacts architecture.
5. Determine the appropriate data recovery solution in Snowflake and how data can be restored.

Data Engineering

1. Determine the appropriate data loading or data unloading solution to meet business needs.
2. Outline key tools in Snowflake’s ecosystem and how they interact with Snowflake.
   Determine the appropriate data transformation solution to meet business needs.

Performance Optimization

1. Outline performance tools, best practices, and appropriate scenarios where they should be applied.
2. Troubleshoot performance issues with existing architectures.

TABLE OF CONTENTS

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)

1. Account Parameters
2. 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.

1. Isolate or segment accounts
2. Key considerations and constraints when defining an account strategy
3. Features/capabilities that can be leveraged across accounts
4. Identify use cases that are appropriate for account strategies

– Configure Role Based Access Control (RBAC) hierarchy

1. Privilege inheritance
2. Database roles
3. System roles and associated best practices
4. Functional roles compared to access roles

– Data Access

Storage integrations

Design an architecture that meets data security, privacy, compliance, and governance requirements.

– Data Security

1. Secure views
2. Column-level security

– Dynamic Data Masking

– Row level security

– Row access policies

1. Compliance
2. Payment Card Industry (PCI) Security Standard
3. Personal Identifiable Information (PII)/ Personal Health Information (PHI)
4. Features of the different Snowflake editions

– Encryption

– Network security

1. Access control lists
2. AWS Private Link/Azure Private Link

Outline Snowflake security principles and identify use cases where they should be applied.

– User, role, grants provisioning

– Authentication

1. Federated authentication
2. Single Sign-on (SSO)
3. Multi-Factor Authentication (MFA)
4. Key-pair authentication
5. 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)

– Use cases

1. Sharing within the same organization/same Snowflake account
2. Sharing within a cloud region
3. Sharing across cloud regions
4. Sharing between different Snowflake accounts
5. Sharing to a non-Snowflake customer
6. Sharing across platforms

Design data sharing solutions, based on different use cases.

– Snowflake Marketplace

– Data Exchange

– Data sharing methods

1. Configure shares, account parameters, and privileges
2. Security patterns for data sharing

Outline the purpose, benefits, and capabilities of the multiple data sharing methods

– Data lake and environments

1. Storage directory structure
2. Zones (data warehouse layers)
3. Support of DevOps/DataOps principles
4. Production/development/sandbox
5. Data workloads
6. Data warehouse
7. ELT/ETL

Create architecture solutions that support development lifecycles as well as workload requirements.

– Development lifecycle support

1. Migration

CI/CD

2. Deployment
3. Rollback process

– Roles

– Virtual warehouses

– Object hierarchy

Databases

CI/CD

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

– 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

1. Data corruption impacts
2. Fail-safe

– Disaster recovery

1. Replication and failover
2. Zero-copy cloning

Data Engineering – 20-25%

Determine the appropriate data loading or data unloading solution to meet business needs.

– Data sources

1. Data at rest
2. Data in motion
3. External sources and formats
4. Streaming data

– Snowpipe

– Change Data Capture (CDC)

1. OLTP/RDBMS sources
2. API sources

– Data ingestion

1. Bulk file upload
2. Snowpipe
3. External tables
4. Reload process
5. Incremental updates compared to full updates
6. Iceberg tables
7. Parameters for copying data and addressing data handling error

– Architecture changes

1. Schema detection and table schema evolution
2. Data source changes

– Data unloading

– Connectors

1. Kafka
2. Spark
3. Python

Outline key tools in Snowflake’s ecosystem and how they interact with Snowflake.

– Drivers

1. JDBC
2. ODBC

– API endpoints

Use of system allowlist

– SnowSQL

– Snowpark

1. Python
2. Scala
3. Java

– Views and tables

1. Benefits, limitations, properties
2. Relationship and impact between the view and data types
3. Impact of costs
4. Dynamic tables

– Staging layers and tables

– Querying semi-structured data

Determine the appropriate data transformation solution to meet business needs.

Flattened

– Data processing

– Stored procedures

– Streams and tasks

– Functions

External functions

– Performance impacts

1. User-Defined Functions (UDFs)
2. User-Defined Table Functions (UDTFs)
3. Secure functions

Performance Optimization – 20-25%

Outline performance tools, best practices, and appropriate scenarios where they should be applied.

– Query profiling

1. Interpret a Query Profile, identify bottlenecks, and outline recommendations
2. Metadata functions

– Virtual warehouse configurations

1. Auto-suspend/resume
2. Scale up/down (resizing)
3. Scale in/out (multi-cluster warehouse/auto-scaling)
4. Query acceleration service
5. Warehouse queuing
6. Snowpark-optimized warehouses

– Clustering

1. Natural clustering
2. Auto-clustering
3. Clustering keys

– Search optimization service

– Caching

1. Different cache layers
2. Cache Expiration
3. Impact of costs

– Use of system clustering information

– Warehouse configurations

– Optimization techniques

– Micro-partition pruning

– Monitoring and alerting

Troubleshoot performance issues with existing architectures.

1. Use of the Account Usage and Information schemas
2. Resource monitoring
3. Email notifications

For more information on SnowPro® Advanced Architect training; please visit here.

Contact Locus IT support team for further training details.