Practice Edurely Dumps to Assure 100% Success in DEA-C01 Exam – 2023

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SnowPro Advanced Data Engineer Certification

DEA-C01

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1100

Candidates Passed DEA-C01 Exam

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Average Score in Real Exam at Testing Center

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DEA-C01 Questions from Edurely in Real Exam

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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Exam Information

SnowPro Advanced Data Engineer Certification
$375 USD
65 Questions
750 + Scaled Scoring from 0 – 1000
115 Minutes
SnowPro Core Certified

Frequently Asked Questions

The SnowPro DEA-C01 exam is easier to tackle if you fully prepare for the course. Candidates with hands-on knowledge of the concepts find it easy to crack the exam.

Usually, it takes 3-4 weeks to prepare for the DEA-C01 exam. The course is designed for candidates who are experienced data engineers.

Domains Percentage
Data Movement 25-30%
Performance Optimization 20-25%
Storage and Data Protection 10-15%
Security 10-15%
Data Transformation 25-30%

To take the SnowPro DEA-C01 exam, follow these steps:

  • Create a Snowflake Certification Portal Account
  • Register for a Snowflake Exam at PearsonVue
  • Take the test 

To prepare for the DEA-C01 exam, follow these steps:

  1. Download the exam guide for the DEA-C01 exam
  2. Study the course from authentic study materials. 
  3. Practice your concept from reliable dumps. 
  4. Revise your concepts. 
SnowPro data engineer certification exam SnowPro data engineer recertification exam
Number of questions 65 40
Exam time 115 minutes 85 minutes
Exam cost  $375 USD  $188 USD

Yes, you can take the DEA-C01 exam at home. The other option is to take the exam at the testing center. 

You would have 3 attempts to take the DEA-C01 exam. You need to pay for each attempt. 

Edurely is the best dump provider of Snowflake exams. We offer the most authentic and reliable exam questions. You would get real exam questions, a money-back offer, free demo questions, customer support service, and PDF file dumps. Get the DEA-C01 dumps for guaranteed success. 

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