By completing the AWS Certified Big Data Specialty Exam, I recently obtained my second AWS certification. I took a similar exam for Google Cloud last year and offered a collection of study tools that helped me pass the exam. In this post, I’ll provide my study guide as well as the strategy I utilised to become certified in a short amount of time. I had passed the Associate Solution Architect certification and had less than a year of experience working with AWS Big Data solutions prior to this test.
Plan Your Research
This AWS certification study plan was created for busy professionals within a tight timeframe. I would extend the study plan to go through the laboratories, acquire hands-on experience, and read through the public case studies for a really deep dive into AWS big data solutions and design best practices.
Courses Available Online
I originally registered in A Cloud Guru’s AWS Certified Big Data Specialty course to get a high-level overview of all of the products and essential ideas because I was unfamiliar with all of the AWS Big Data products. I listened at 2x speed and skimmed through the related whitepapers and documents in the resources area to review each course.
Whitepapers or Youtube re: Invent Videos
Although AWS provides extensive online documentation for each of its Big Data products, watching the re: Invent videos or reading selected whitepapers recommended on A Cloud Guru saved me time and allowed me to focus on the important design considerations rather than the low-level details that were not tested on the exam. Pay close attention to the illustrations and comparative charts, as well as the product limits.
Important Websites
- Amazon DynamoDB deep dive – Advanced design pattern at AWS re: Invent 2019
- Building a streaming data platform with Amazon Kinesis @ AWS re: Invent 2019
- AWS re: Invent 2019: Amazon Redshift deep dive and best practices
- At AWS re: Invent 2019, take a deep dive into running Apache Spark on Amazon EMR.
- Sessions on AWS Big Data and Analytics at Re: Invent 2018
Security and Hadoop Toolset Developer Guide
To memorise the encryption choices, backup methods, and cross-region replication, go through the security part of the developer manuals for each of the AWS products. This part will be primarily memorization unless you have hands-on experience designing for various encryption limitations or developing global databases with cross-region backups at work. The Hadoop ecosystem is no exception. Therefore, Understand whether to utilise Presto vs. Hive, as well as high-level explanations for the most common Hadoop tools.
Important Links:
Practice Exams
Test preparedness questions and free sample exam questions are available on the official AWS training and certification website. Those examinations were less large data-focused, but still a solid depiction of AWS-style problems, in my opinion. Study4Exam also sold practice tests, which I purchased. Don’t get dismayed if you receive a poor score on the practice examinations because the test format differs from the official exam (On the real test, there are no multiple-choice problems in which you must pick four right answers from six alternatives). The most crucial thing was to find knowledge gaps for various items or concepts.
Study Guide
Kinesis, EMR, Data Pipeline, DynamoDB, QuickSight, Glue, Redshift, Athena, and AWS Machine Learning services were all severely tested, therefore I prepared a study guide to go over them. On the real test, the key elements were EMR, Redshift, and DynamoDB, in that sequence. Focus on the following topics for each product:
- Kinesis: Data Streams vs. Firehose vs. Video Streams vs. Data Analytics are the contrasts in Kinesis. The principles and best practices for gathering data include KPL (aggregation/collection), KCL, and Kinesis Agents.
- DynamoDB: Table design (WCU/RCU, GSI/LSI), encryption and security, and performance optimization following best practices
- EMR: Hadoop ecosystem, encryption and security choices, and selecting the optimal performance formats
- RedShifts: Best practices for loading, copying, updating, and deleting data in Redshift. Options for access control, encryption, security, and replication
- Others: A high-level grasp of each product and how it relates to big data (for example, utilizing Lambda to filter data or route data to S3/Redshift).
Final Verdict
In the end, I must say that passing the Big Data Certified Specialty exam is not an easy task. Therefore, You have given proper dedication and time to pass the exam. I hope all the resources that I have mentioned will help you all to prepare for your exam easily.
Best of Luck to All!
