The DEA-C01 is a core intermediate certification in the AWS data engineering field, focusing on practical data pipeline building and end-to-end data processing capabilities.

1. Introduction to the Microsoft Azure DevOps Solutions certification

AWS Certified Data Engineer Associate (DEA-C01) is a mid-level data engineering certification launched by Amazon Web Services (AWS) in 2023, focusing on verifying practitioners' end-to-end practical abilities in designing, building, automating, and operating data pipelines based on AWS services, and achieving data analysis and visualization.

It is the first intermediate qualification in the AWS certification system specifically designed for data engineers, filling the capability gap between "data foundation" and "advanced data architecture." Its aim is to cultivate intermediate data talents who can adapt to enterprise data-driven needs and use the AWS toolchain to solve practical data engineering problems.

In the digital transformation of enterprises, data is the core asset, but raw data needs to go through the entire process of "collection cleaning conversion storage analysis" in order to be transformed into valuable information for decision-making. This process requires professional data engineers to build stable, efficient, and scalable data pipelines.

The core of DEA-C01 certification is to cultivate "practical data pipeline builders in the AWS ecosystem" rather than simply "data tool users." The certificate holder needs to master the collaborative application of AWS core data services, be able to design data engineering solutions based on business scenarios, solve key problems such as data transmission delay, incompatible formats, high storage costs, and low analysis efficiency, and ensure the safe, efficient flow and value realization of data in the AWS environment.

When building a user behavior analysis data pipeline for e-commerce platforms, DEA-C01 certificate holders can use Kinesis Data Firehose to collect real-time user behavior logs from the app and transmit them to S3 Data Lake for raw data storage; use Glue ETL to convert unstructured logs into structured data and output it to the Redshift data warehouse; perform data quality verification through Glue DataBrew.

2. The Competitive Edge of an DEA-C01 Certification

DEA-C01 is AWS's first intermediate certification specifically designed for data engineers, filling the "competency certification gap" in data engineering positions When companies recruit AWS data engineers, they often list them as a "priority or even a necessary condition," especially in data-driven industries, where they are highly recognized and serve as the "gateway" to enter the AWS data ecosystem.

DEA-C01 certification covers the entire process of data engineering, and the learning process can help practitioners establish a "cloud native data engineering mindset" and master flexibility Serverless, the unique data processing mode of cloud computing, such as Hucang integration, solves the pain points of traditional data engineering in resource expansion, cost control, and flexibility.

Holders of DEA-C01 certification can join the AWS Data Engineer Community to obtain official data engineering best practice documents and industry cases; priority participation in AWS Data Technology Summit and offline salons, connecting with experts in the same field and high-end project opportunities, laying the foundation for advanced senior data engineers or data architects.

3. Core Components of the DEA-C01 Certification

For IT professionals who are committed to becoming data architects, data engineers, or wish to master large-scale data processing and analysis, the AWS Certified Data Engineer Associate (DEAC01) certification is a highly targeted proof of professional competence.

DEA-C01 certification focuses on the full process practice of designing, building, and maintaining end-to-end data pipelines on AWS cloud, aiming to verify whether you have complete technical capabilities from data collection to value delivery. It is an important competency benchmark for data professionals in the AWS technology stack.

The core of designing a data storage solution lies in selecting the appropriate storage solution based on the data application scenario. You need to master the construction of an economically efficient data lake based on S3, deploy high-performance data warehouses and optimize table structures using Redshift, and flexibly choose RDS, DynamoDB, and ElastiCache for transactional, caching, and other scenarios to achieve a modern architecture of "lake warehouse integration."

The design of data conversion and processing solutions is the core and difficulty of authentication. You will learn to use Glue ETL for large-scale batch processing, utilize Kinesis Data Analytics for real-time stream processing, and use tools such as Glue DataBrew to ensure data quality, cleaning and transforming raw data into reliable datasets for analysis.

The data analysis and visualization solution design module focuses on the ultimate presentation of data value. You need to master the use of QuickSight to create interactive dashboards and provide self-service analysis capabilities for business users; at the same time, Athena can be used to perform ad hoc queries on data lakes and seamlessly integrate processed data with machine learning services such as SageMaker.

Excellent engineering capabilities cannot be achieved without automation and governance. You need to be proficient in using Step Functions and EventBridge to orchestrate complex data workflows and governance systems through tools.

4. What are the requirements to be an AWS Certified Data Engineer – Associate?

(1) Qualification prerequisites:

To obtain DEA-C01 certification, we recommend that you have 6-12 months of practical experience in AWS data services and be familiar with the configuration and use of core data services.

It is recommended that you have a basic understanding of data engineering concepts and basic SQL programming skills, and prioritize passing the AWS Cloud Practitioner (CLF-C02) certification to solidify your AWS foundational knowledge. 

(2) Training and examinations:

DEA-C01 has a total of approximately 65 questions, including multiple-choice questions and scenario analysis questions for designing data pipeline solutions based on business scenarios. The exam lasts for 130 minutes, including 10 minutes of pre exam instructions and a 5-minute survey questionnaire.

The maximum score for the exam is 1000 points, and passing with a score of 720 or above will incur an exam fee of approximately $150. 

(3) Qualification maintenance:

The DEA-C01 certificate is valid for 3 years and must be renewed within the validity period by passing the "renewal exam" or obtaining a higher-level AWS certification.

5. Comparable Certifications to AWS Certified Data Engineer – Associate Certification

• Alibaba Cloud ACP—Big Data Engineer
• Huawei HCIP—Big Data Developer
• Google Cloud Professional Data Engineer