Snowflake Data Engineering Preparations Course- DEA-C02 | Udemy [Update 05/2026]
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Genre: eLearning[/center]

What you'll learn:
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[*]Create and configure a Snowflake environment from scratch
[*]Navigate and use Snowsight UI and SQL Editor effectively
[*]Execute SQL queries using both Snowsight and SnowSQL
[*]Create databases, schemas, tables, stages, and file formats
[*]Understand data loading and data unloading concepts in Snowflake
[*]Work with internal stages, named stages, and COPY INTO commands
[*]Understand modern data loading patterns and near real-time ingestion concepts
[*]Handle data validation and loading errors using Snowflake loading options
[*]Learn Streams, CDC (Change Data Capture), and Task scheduling concepts
[*]Learn Time Travel, retention periods, Fail-Safe, and Zero-Copy Cloning
[*]Understand replication and cloning concepts in Snowflake
[*]Create and use User-Defined Functions (UDFs)
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This course contains the use of artificial intelligence.

Welcome to the Snowflake Data Engineering Preparations Course DEA-C02
, a practical and beginner-friendly course designed to help you build strong Snowflake data engineering skills while preparing for the SnowPro Advanced: Data Engineer Certification (DEA-C02)
.

This course is designed for:

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[*]aspiring data engineers
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[*]SQL developers
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[*]ETL developers
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[*]cloud professionals
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[*]analytics engineers
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[*]students preparing for Snowflake certifications
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[*]anyone interested in modern cloud data engineering
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Whether you are completely new to Snowflake or already have some experience with SQL and data platforms, this course will guide you step-by-step through the core concepts used in real-world Snowflake environments.

Throughout this course, you will learn how to work with Snowflake using practical examples, hands-on SQL demonstrations, and simplified explanations of important data engineering concepts.

We begin with the fundamentals by creating a Snowflake trial account and exploring the Snowflake user interface, SQL editor, and workspaces. You will learn how to execute SQL queries using both Snowsight and SnowSQL, manage SQL scripts efficiently, and work with query history and result options.

From there, we move into one of the most important areas of modern data engineering: data loading and data movement
. You will learn:

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[*]stages
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[*]internal and named stages
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[*]file formats
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[*]COPY INTO commands
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[*]data loading patterns
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[*]data unloading
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[*]SnowSQL-based ingestion
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You will also understand how Snowflake handles structured and semi-structured data and how to manage CSV files and file format configurations properly.

The course also covers error handling and validation
, helping you understand how to detect bad records, validate incoming data, and manage failed loads using options such as:

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[*]CONTINUE
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[*]SKIP_FILE
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[*]ABORT_STATEMENT
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[*]VALIDATION_MODE
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As you progress further, you will explore important Snowflake architecture and performance optimization concepts such as:

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[*]micro-partitions
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[*]pruning
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[*]clustering
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[*]caching mechanisms
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[*]query profiling
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These topics are extremely important for understanding how Snowflake processes data internally and how query performance can be improved in large-scale environments.

This course also includes several important Snowflake data protection and recovery features including:

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[*]Time Travel
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[*]retention periods
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[*]Fail-Safe
[/list]

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[*]Zero-Copy Cloning
[/list]

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[*]database/schema/table cloning
[/list]

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[*]data replication concepts
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You will understand how Snowflake provides backup, recovery, and environment cloning capabilities without traditional storage duplication.

Security is another major focus area in this course. You will learn key security concepts including:

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[*]Role-Based Access Control (RBAC)
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[*]Dynamic Data Masking
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[*]Network Policies
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[*]data governance controls
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Using practical examples, you will understand how organizations secure sensitive data in Snowflake environments.

One of the most valuable sections of this course focuses on modern incremental data engineering pipelines using:

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[*]Streams
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[*]Change Data Capture (CDC)
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[*]Tasks
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[*]Streams + Tasks patterns
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[*]Incremental ELT pipelines
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You will learn how Snowflake supports near real-time data processing and automated incremental workflows using built-in cloud-native features.

Finally, the course introduces advanced development concepts such as:

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[*]User-Defined Functions (UDFs)
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[*]Stored Procedures
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[*]Snowpark concepts
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[*]procedural logic
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These topics help you understand how complex business logic and advanced data transformations can be implemented directly inside Snowflake.

By the end of this course, you will have a strong understanding of Snowflake data engineering concepts and be better prepared for the SnowPro Advanced Data Engineer DEA-C02 certification exam as well as real-world Snowflake data engineering projects.

If you want to learn Snowflake in a simple, practical, and hands-on way while building strong data engineering fundamentals, this course is for you.

Who this course is for:
Beginners interested in learning Snowflake
Aspiring Data Engineers
SQL Developers and ETL Developers
Cloud and Data Professionals
Developers moving from traditional databases to cloud data platforms
Anyone interested in modern cloud-based data engineering and ELT pipelines

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