Overview
Master the data game: Learn data ingestion, transformation & storage on AWS for your data engineer cert., Ace the exam: Demystify key concepts & practice with realistic AWS data engineering scenarios. Master serverless data pipelines for agility & cost efficiency., Unlock career opportunities: Be industry-ready with the in-demand skills of an AWS data engineer., Join the data elite: Get certified & land your dream job as an AWS data engineer. Unlock the secrets of data lakes, warehouses & analytics on AWS.
Want to get AWS certified but don't know where to start or want to get it within a target date
The course is designed for beginners, so no prior experience with AWS or data engineering is required. However, some familiarity with coding is helpful.
Ace the NEW AWS Certified Data Engineer Associate (DEA-C01) exam with this groundbreaking practice course - the first of its kind! Learn from detailed explanations by Ex-Amazon Data Architect. A 30-day money-back guarantee if you're anything less than thrilled.
Conquer 4 module wise tests (with 100 questions each) and an unique 65 question real-exam like practice exams with 450+ realistic, scenario-based questions, mirroring the actual exam's structure and domains.
Designed by Ananth Tirumanur, who is Ex-Amazon Data Architect, and has helped numerous clients design and build their data architecture.
Deep-dive explanations for every answer, and links to AWS documentation for deeper insights - not just revealing the right choice, but boosting your understanding for long-term mastery. It's not just about practicing; it's about understanding the 'why' behind each answer.
In addition, join a live meeting with instructor to address any additional questions
ď¸ Stay up-to-date with content aligned with the official exam guide and AWS sample questions.
Unravel complex concepts with detailed explanations for each option, solidifying your knowledge and exposing the flaws of incorrect answers.
Backed by direct AWS documentation references, ensuring reliable and in-depth learning. ď¸
Be the first! Gain an unmatched edge with this pioneering practice suite.
Launch your career! This course will empower you to confidently pass the exam and unlock exciting AWS Data Engineering opportunities.
Don't wait! Upgrade your skills and join the ranks of top AWS Data Engineers. Enroll now!
As your exam date approaches, our practice exams are the perfect tool to polish your preparation. Scoring high here means you're ready to ace the real deal!
Your feedback fuels our progress. We're constantly refining our questions based on your input and our firsthand experience with AWS exams.
Ananth Tirumanur
Demonstrated leadership in Data related Technical Programs. 17 years of Proficiency in data management, analytics and visualization, data flow, data integrity, data automation and data science.
Currently working at Amazon Web Services as a Senior Data Architect.
In my role at AWS, I was responsible for leading a team of engineers in the design, implementation, and maintenance of a large-scale data lake. I have a deep understanding of the full data engineering lifecycle, from data collection to data analysis and visualization. My core skills are with Python, Pyspark, Hadoop, Hive, cloud infrastructure, batch and streaming data. I am also proficient in a variety of data engineering tools and technologies, including AWS, Redshift, Snowflake, Postgres, MySQL, CloudFormation, CDK, Terraform, and CI/CD tools. Here are some of the highlights from my previous role:
Developed and popularized reusable solutions that reduced data lake build costs by 80%. This was achieved by creating a library of reusable code and templates that could be used to quickly and easily build data lakes. The library was made available to all engineers, which saved them time and effort in building their own data lakes.
Developed reusable assets and published guidance in aws-samples (Github) and AWS documents. This helped to ensure that other engineers could easily find and use the reusable assets that I had developed. The aws-samples repository is a great resource for finding reusable assets, and the AWS documentation is a great resource for learning about how to use AWS services.