AWS Data Engineer associate Certification preparation demands consistent study and unwavering dedication.
Before preparing for the DEA-C01 exam, you have a lot of questions popping up in your head, like:
- How to pass the AWS data Engineer associate exam?
- How long does it take to prepare for AWS data Engineer associate certification?
- Which study resources to rely upon?
Relax, we’ve got you covered.
In this blog post, we explore necessary AWS Data Engineer associate exam tips, the target audience for the DEA-C01 exam, strategic tips for AWS Data Engineer Associate Certification, and the AWS Data Engineer certification path in detail.
Let’s dig in to know more!
Data Engineering on AWS
The field of data engineering rises daily, which increases the demand for Data engineers. It has been found that there will be a 45% increase in job listings globally between 2021 and 2024, and this growth will improve by 28% in the upcoming ten years.
With this new AWS Certification, individuals can position themselves for data engineering jobs that are in high demand.
AWS Data engineers require an architectural grasp of AWS services linked to data, as well as the programming skills of a developer. While some data engineers pursue careers in data engineering exclusively, others may be drawn into them by chance.
An Overview of AWS Data Engineer Associate (DEA-C01) Certification
AWS Certified Data Engineer – Associate Certification validates your proficiency with key AWS data services. It demonstrates how well you can manage monitoring and troubleshooting, build data pipelines, and optimize cost and performance while following industry best practices.
To ensure that applications operate properly, data engineers are primarily involved in building, maintaining, and updating the AWS cloud architecture. The demand for AWS Data Engineers expanded dramatically due to the tasks associated with Data Engineering.
This exam offers a special opportunity to be among the first to obtain this recently released certification if you’re interested in using AWS technology to turn data into insightful research.
To pass the DEA-C01 exam with flying colors, follow the AWS Data Engineer Associate Certification Preparation tips mentioned below.
Also Read : How to Become an AWS Data Engineer – A Complete Guide [2024]
DEA-C01 AWS Certified Data Engineer – Associate Exam Domains
AWS Certified Data Engineer Associate exam guide includes data such as domains, task statements, and exam weightings.
The domains and weights covered in the DEA-C01 exam are as follows:
Domain 1: Data Ingestion and Transformation (34%)
As it covers a major percentage of the AWS Certified Data Engineer – Associate Exam syllabus, it is essential to spend considerable time on it. It is advisable to spend about 40-45 hours to completely through this section.
Domain 2: Management of Data Stores (26%)
This domain is also substantial, comprising 26% of the exam syllabus. Allocate approximately 30-35 hours of your preparation time to comprehensively cover the topics related to data store management.
Domain 3: Support and Data Operations (22%)
Plan to invest 20-25 hours of your study time to understand the support and data operations aspects thoroughly.
Domain 4: Data Governance and Security (18%)
Allocate around 15-20 hours of your study time to thoroughly understand the concepts in this domain.
8 AWS Data Engineer Associate Exam Tips
To become a skilled AWS Data Engineer, it’s essential to follow a structured learning path. The key to passing the AWS Certified Data Engineer – Associate examination is to prepare strategically and concentrate mentally.
Let’s look at a few Exam tips for DEA-C01 certification and learn how to make the most of your time, handle challenging questions, and get over exam anxiety:
1. Explore the AWS Data Engineer Associate Certification study guide
As a first step in exam preparation, explore the AWS Data Engineer Certification study guide and familiarize yourself with the exam objectives and format.
Review the exam domains mentioned in the study guide and get familiar with the exam concepts.
After gaining a thorough understanding of the concepts in the theoretical part, opt for practical exposure.
2. Plan your study schedule
Set dedicated time slots in your calendar specifically for studying. Consider your work hours, personal commitments, and peak productivity times to create a realistic and achievable schedule.
Divide the exam syllabus into manageable sections and allocate study sessions for each topic accordingly. Strive for consistency by sticking to your study schedule religiously.
| Domain | Percentage | Study Time per week |
| Data Ingestion and Transformation | 34% | 5-6 hours |
| Management of Data Stores | 26% | 4- 5 hours |
| Support and Data Operations | 22% | 3-4 hours |
| Data Governance and Security | 18% | 2-3 hours |
Remember to be flexible and adjust your plan as needed based on your progress and evolving priorities.
By planning your study schedule effectively, you’ll ensure adequate coverage of all exam prerequisites and domains while maintaining a healthy work-life balance.
3. Take Online Courses
Preparing for the AWS Certified Data Engineer Associate certification exam doesn’t have to be daunting, especially if you’re already well-versed in AWS cloud fundamentals.
If you’ve had prior experience with the AWS Cloud platform, self-study can often be adequate for passing the exam.
If you are a fresher just stepping into the AWS Data Engineering field, then you can take the following online courses:
- AWS Certified Data Engineer Associate: By enrolling in this course, you can gain access to 120+ Unique AWS Data Engineer Certification Practice Exam Questions, video courses, labs, and a sandbox.
- Data Engineering in AWS: By taking this course, you can grasp skills in data engineering, machine learning, and AWS.
However, enrolling in online classes and training can provide additional insights and deepen your understanding of core principles.
By combining self-study with online courses, you’ll enhance your comprehension of fundamental concepts, thereby increasing your readiness to ace the DEA-C01 exam.
4. Strengthen your basics
Starting from scratch is one of the best ways to shine in any career. Therefore, it is recommended to start from the basics of data engineering.
- Cloud Computing Fundamentals: Start by understanding the basics of cloud computing, its advantages, and core services.
- Programming Proficiency: You can master programming languages like Python and SQL to create data pipelines and interact with databases.
- Data Analytics Concepts: Get familiar with the basics of data analysis, statistics, and data modeling.
5. Explore AWS in Depth
After strengthening your basics, it is essential to know in-depth about AWS. It is advisable to improve your key skills in the following areas:
- AWS Cloud Essentials: It is important to familiarize yourself with AWS services such as S3, EC2, VPC, and IAM. AWS comes up with a Cloud Essentials training path with detailed tutorials and hands-on labs.
- Amazon Redshift: Get familiar with the data warehousing technology by constructing data pipelines for loading and querying data. Furthermore, you can make use of AWS Redshift Hands-on Labs and guidance resources.
- AWS Glue and Lambda: Proficient in serverless data pipelines using Glue for data extraction, transformation, and loading, and AWS Lambda for serverless processing can be beneficial. AWS Glue Labs and Serverless Application Model (SAM) tutorials offer practical experience.
- AWS Data Pipeline Services: You must get familiar with AWS services such as Kinesis Firehose for data streaming, Amazon DynamoDB for NoSQL databases, and CloudWatch to monitor data pipelines via dedicated AWS documentation and blogs.
- Security and Compliance: Familiarize yourself with AWS security best practices and compliance requirements for data protection via AWS Security Fundamentals training and whitepapers.
- Data Engineering Best Practices: Know the current industry trends and data engineering emerging technologies by attending webinars, reading blogs such as AWS Big Data blog, and following thought leaders in the field.
Successful AWS Data Engineer Certification preparation involves mastering various AWS services.
It is recommended to devote your learning time to study the following AWS services:
- Amazon Athena
- Amazon Redshift
- Amazon QuickSight
- Amazon EMR
- AWS LakeFormation
- AWS EventBridge
- AWS Glue
- AWS Glue DataBrew
- All AWS Glue features
- Amazon Kinesis
- Amazon Kinesis Data Firehose
- Amazon Kinesis Data Streams
- Amazon Managed Service for Apache Flink
- Amazon Managed Streaming for Apache Kafka (Amazon MSK)
6. Improve your hands-on skills
Practice with real-world scenarios and projects is essential for AWS Data Engineer Certification readiness. Engage with AWS hands-on labs and real-time projects to apply theoretical knowledge in practical situations, reinforcing your understanding of key concepts.
Whizlabs’ hands-on lab’s feature offers interactive and practical learning experiences in real-time settings.
You can also improve your hands-on skills by following the below steps:
- Create cloud-based data pipelines for real-world scenarios such as analyzing web traffic or processing sensor data. This hands-on approach enhances your skills and strengthens your portfolio.
- Involve in Cloud-focused hackathons such as AWS DeepRacer to engage with others and tackle time-bound challenges to refine your skills under pressure.
- Consider taking AWS foundational certifications such as AWS Certified Cloud Practitioner or AWS Certified Solutions Architect – Associate to validate your cloud knowledge and demonstrate your skills in this platform.
7. Join study groups
Make use of study groups or communities dedicated to AWS Data Engineering Certification preparation. In this period, you can interact with peers who share similar goals, and provide valuable insights, support, and motivation throughout your learning journey.
8. Take a practice test
It is one of the best ways to assess your exam readiness. It simulates a real exam and you can eliminate the fear while appearing for the exam by boosting your confidence level.
Whizlabs offers 120+ Practice questions to allow candidates to simulate real exam conditions and gauge their readiness effectively.
After completing the practice test, review your answers and identify areas where you may need further study or practice. Repeat this process regularly to track your progress and build confidence for the actual exam.
Adhering to these AWS Data Engineer Certification preparation tips can help to increase your success rate in clearing the exam.
Also Read : AWS Data Engineer Associate Salary in 2024
Target Audience for AWS Data Engineer Associate(DEA-C01) Certification
The AWS Certified Data Engineer – Associate (DEA-C01) exam is designed for those with 2-3 years of expertise in AWS data engineering and a minimum of 1-2 years of hands-on skills with AWS services, according to the DEA-C01 exam guide issued by Amazon.
AWS added that applicants need to be skilled in managing the effects of speed, volume, and diversity of data on tasks like data ingestion, transformation, modeling, security, governance, and privacy, as well as schema design and the creation of the best possible data storage solutions.
FAQs
Is coding required for an AWS data engineer?
Yes, coding is essential for individuals pursuing a career as an AWS Data Engineer.
What tasks does an AWS data engineer perform?
AWS data engineers can handle data engineering duties within the Amazon Web Services cloud platform. Their primary responsibility is to create, maintain, and upgrade AWS cloud infrastructure to support application operations.
Is AWS a suitable platform for Data Engineers?
Absolutely. AWS can be a great choice for data engineers as it contains all the necessary data engineering tools. These tools can streamline the process of data pipeline construction, manage data transfers, and ensure efficient data storage solutions on the AWS platform.
What skills does an AWS data engineer need?
To excel as an AWS Data Engineer, you must possess key skills in SQL, data modeling, Hadoop for big data, Python, and proficiency in AWS cloud services.
What does AWS Data Engineering involve?
AWS Data Engineering is primarily involved in tasks such as data collection from diverse sources, data storing and processing, performing analysis, creating visualizations, and building AWS pipelines.
What are the main responsibilities of a data engineer within AWS?
The core responsibilities of AWS Data Engineer include collecting data from various sources, designing storage solutions, constructing processing pipelines, analyzing data, creating visualizations, managing pipelines, and optimizing performance.
Conclusion
We trust that this blog post provides a thorough outline of AWS data engineer associate exam tips.
If you have coding proficiency and aspire to become an AWS data engineer, you’ve likely identified a promising career path. This role presents opportunities to address some of the most intricate and groundbreaking challenges in today’s data engineering landscape.
Familiarize yourself with the Whizlabs hands-on labs offered to refine your practical skills.
If you’re considering pursuing any other AWS Certification, begin your enrollment today. Wishing you the best of luck with your exam preparation!
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