Latest SnowPro Advanced Data Engineer Certification DEA-C01 Dumps 2023

The SnowPro Advanced Data Engineer Certification with the exam code DEA-C01 will access advanced knowledge and skills to apply updated data engineering principles by utilizing Snowflake. This certification will evaluate the ability to:

• Source data from Data Lakes, APIs, and on-premises
• Transform, replicate, and share data across cloud platforms
• Design end-to-end near real-time streams
• Design scalable compute solutions for DE workloads
• Evaluate performance metrics

Course Overview 

• Certification Name: SnowPro Advanced: Data Engineer 
• Exam Code: DEA-C01
• Total Number of Questions: 65
• Question Types: Multiple Select, Multiple Choice
• Time Limit: 115 minutes
• Languages: English
• Registration Fee: USD 375
• Passing Score: 750 + Scaled Scoring from 0 – 1000
• Prerequisites: SnowPro Core Certified

Targeted Audience of SnowPro DEA-C01 Exam

This exam is specially designed for data engineers who want to learn and groom their data management and processing skills.  

What Are The Prerequisites To Take SnowPro DEA-C01 Exam?

The candidates who are aspiring to take DEA-C01 exam must have the following:

• 2+ years of data engineering experience
• Practical experience using Snowflake for DE tasks
• Working knowledge of Restful APIs, SQL, semi-structured datasets, and cloud-native concepts. Programming experience is a plus.

Detailed Course Outline 

1-  Domain: Data Movement

1.1 Given a data set, load data into Snowflake.

• Outline considerations for data loading
• Define data loading features and potential impact

1.2 Ingest data of various formats through the mechanics of Snowflake.

• Required data formats
• Outline Stages

1.3 Troubleshoot data ingestion.

1.4 Design, build, and troubleshoot continuous data pipelines.

• Design a data pipeline that forces uniqueness but is not unique
• Stages
• Tasks
• Streams
• Snowpipe
• Auto ingest as compared to Rest API

1.5 Analyze and differentiate types of data pipelines.

• Understand Snowpark architecture (client vs server)
• Create and deploy UDFs and Stored Procedures using Snowpark
• Design and use the Snowflake SLQ API

1.6 Install, configure, and use connectors to connect to Snowflake.

1.7 Design and build data sharing solutions.

• Implement a data share
• Create a secure view
• Implement row level filtering

1.8 Outline when to use External Tables and define how they work.

• Partitioning external tables
• Materialized views
• Partitioned data unloading

2- Domain: Performance Optimization

2.1 Troubleshoot underperforming queries.

• Identify underperforming queries
• Outline telemetry around the operation
• Increase efficiency
• Identify the root cause

2.2 Given a scenario, configure a solution for the best performance.

• Scale out as compared to scale in
• Clustering as compared to increasing warehouse size
• Query complexity
• Micro partitions and the impact of clustering
• Materialized views
• Search optimization

2.3 Outline and use caching features.

2.4 Monitor continuous data pipelines.

• Snowpipe
• Stages
• Tasks
• Streams

3- Domain: Storage and Data Protection

3.1 Implement data recovery features in Snowflake.

• Time Travel
• Fail-safe

3.2 Outline the impact of Streams on Time Travel.

3.3 Use System Functions to analyze Micro-partitions.

• Clustering depth
• Cluster keys

3.4 Use Time Travel and Cloning to create new development environments.

• Backup databases
• Test changes before deployment
• Rollback

4- Domain: Security

4.1 Outline Snowflake security principles.

• Authentication methods (Single Sign On (SSO), Key Authentication, Username/Password, Multi-factor Authentication (MFA))
• Role Based Access Control (RBAC)
• Column Level Security and how data masking works with RBAC to secure sensitive data

4.2 Outline the system defined roles and when they should be applied.

• The purpose of each of the system defined roles including best practices usage in each case
• The primary differences between SECURITYADMIN and USERADMIN roles
• The difference between the purpose and usage of the USERADMIN/SECURITYADMIN roles and SYSADMIN

4.3 Manage Data Governance.

• Explain the options available to support column level security including Dynamic Data Masking and External Tokenization
• Explain the options available to support row level security using Snowflake Row Access Policies
• Use DDL required to manage Dynamic Data Masking and Row Access Policies
• Use methods and best practices for creating and applying masking policies on data
• Use methods and best practices for Object Tagging

5- Domain: Data Transformation

5.1 Define User-Defined Functions (UDFs) and outline how to use them.

• Secure UDFs
• SQL UDFs
• JavaScript UDFs
• Returning table value compared to scalar value

5.2 Define and create External Functions.

• Secure external functions

5.3 Design, build, and leverage Stored Procedures.

• Transaction management

5.4 Handle and transform semi-structured data.

• Traverse and transform semi-structured data to structured data
• Transform structured to semi-structured data

5.5 Use Snowpark for data transformation.

• Query and filter data using the Snowpark library
• Perform data transformations using Snowpark (ie., aggregations)
• Join Snowpark dataframes

How Much Can You Earn After Gaining Snowpro Data Engineer Certification?

A SnowPro Data Engineer makes an average earning of $120,000 per annum. The salary usually ranges from $80K to $180K.

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