aws certification

My learning path for AWS Certified Data Analytics – Specialty

Recently, I passed AWS Certified Data Analytics – Specialty exam. It’s my 4th AWS certification and toughest one so far (as expected). While, I took this exam to learn best practices & validate myself in-depth on AWS Big Data & Analytics services, the motivation was to build upon existing knowledge in this domain since I have been using few of these services in past/current projects.

Following were the study materials and resources, I used for my preparation.

Online Courses

  • As recommended by many, I too started with AWS Certified Data Analytics Specialty 2020 – Hands On! course on udemy. This course provides good overview of the services in AWS analytics and helps in pointers for further study in detail. By the way, exam covered lot of detailed questions so I believe updating this course will be super helpful.
  • Free digital training courses by AWS – There are many good courses for Big Data and Analytics out of which I highly recommend “Exam Readiness: AWS Certified Data Analytics – Specialty” and “Best Practices for Data Warehousing with Amazon Redshift”
  • AWS re:Invent recent videos related to Big Data especially Redshift and QuickSight.

White Papers

Blogs – AWS big data blog has many gems which one should be familiar with irrespective of any exam prep. I also recommend to implement few use cases to understand analytics on AWS in detail.

Practice testwhizlabs

Summary

Given that it’s specialty exam, prepare in-depth by implementing sample projects and getting started tutorials. It will be big advantage if you are hands-on in how various services can be stitched into a pipeline (batch vs streaming). There are many similar looking services, so reading their FAQs and knowing AWS recommended use cases, patterns and anti-patterns of each services will be very useful.

  • Glue and its integration with Athena, S3, EMR and Redshift
  • Redshift and Redshift Spectrum
  • EMR and EMRFS
  • QuickSight chart types and supported data sources
  • Kinesis and its integration with Lambda, S3 and ElasticSearch
  • Common troubleshooting tips (Provided in AWS doc of each services)
  • Security – At rest and in transit support by services

Hope this was helpful, wishing you all the best.

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