- Learning AWS Cloud changed my life completely. AWS is a leading provider with vast market segment. It can help you grow exponentially in your career. Focus on top Services for data engineering. Learn and get certified in AWS, and build end-to-end projects. S3 is your go-to for storing data. RDS simplifies database management. Glue helps with ETL job processing. EMR is for distributed processing. Lambda for event-based code running. Redshift for analytical workloads. Kinesis for real-time data processing. Dynamo for unstructured data. DMS for data migration. ews also offers other essential services for security and management. Start with AWS Cloud Practitioner certification, then Data Engineering Associate, and explore further options. Get certified to boost your market value. Lastly, build your resume with end-to-end projects like the Spotify data pipeline, data analytics, and Twitter data pipeline using airflow. These projects will give you a solid understanding of data engineering projects on AWS. Happy learning! ππ₯
Here’s your complete guide to learning AWS Cloud and increasing your market value as a data engineer. This article will cover the top 10 services you need to focus on, certification paths, and three end-to-end projects to help you understand the data engineering process easily.
π Overview of Top AWS Services for Data Engineering
As a data engineer, you don’t need to know all the services offered by AWS. It’s important to focus on the highly used services for data engineering and fundamental services. Let’s start by understanding the core services you need to focus on.
| Service | Description |
|---|---|
| Amazon S3 | Store any type of file and build your data lake. |
| RDS | Access to different relational databases and Amazon’s own database service. |
| AWS Glue | Easily process your data on a large scale without worrying about backend servers. |
| EMR | Process huge volumes of data using distributed processing. |
| Amazon Athena | Query data directly on top of existing files like CSV or JSON. |
π Certification and Learning Path
Once you’ve understood the core services, it’s important to prepare for AWS certifications. The certification path for data engineers includes: AWS Cloud Practitioner, AWS Data Engineering Associate, AWS Solution Architect Professional, and AWS Database Specialty. Here’s how you can get started:
- Create an AWS account for free and get comfortable with the AWS UI.
- Complete AWS Cloud Quest Cloud Practitioner for a gamified learning experience.
- Prepare for the certification exams using free resources available on platforms like freeCodeCamp, Coursera, and Udemy.
π Free Resources for Certification Preparation
Explore free resources available on freeCodeCamp, Coursera, and Udemy to prepare for AWS certifications.
π‘ Building End-to-End Projects
To enhance your learning, it’s crucial to work on end-to-end projects related to data engineering. Here are three AWS projects to get you started:
- Spotify Data Pipeline
- Data Analytics
- Twitter Data Pipeline using Airflow
Completing these projects will give you a clear understanding of how data engineering projects are built on the AWS cloud.
π Start Building Your Resume
Once you’ve gained knowledge and completed your projects, it’s time to prepare for data engineering interviews and build your portfolio. Check out the video guide provided in this article to prepare for data engineering interviews and increase your market value.
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