Recently I took both the AWS Big Data exam (now retired) and its new version the Data Analytics. I passed both. I would rate the difficulty level for both exam as moderate.
Exam guide for the certification can be found here and Sample Questions.
Differences between Big Data & Data Analytics Exam
- Amazon MSK is featured on the new exam
- More storage questions on the Data Analytics exam
- A lot more questions on processing
- The Big Data exam used to have a number of Machine Learning questions. You may still see few Machine Leaning questions on the exam
- Relatively fewer questions on Analysis and Visualization
Preparation Tips:
1. If you have passed at least an associate exam, your focus should be on Collection, Processing and Analytics and Visualization domains
2. Know the use cases for each big data analytics service(listed in the next section)
3. Know the anti-patterns for each service
4. Data Analytics certification focuses on OLAP while the Database is OLTP biased. NB: There are OLTP questions on the Data Analytics exam
5. You should understand how to secure the services. Know which ones use fine grained IAM permissions and which ones do not
6. Understand how encryption at rest and in-transit works and which types are supported for each service
7. You should have experience with Redshift and know the best practices in designing tables and loading data for optimum performance
8. Services used for Batch Processing and Streaming
9. Know the license models for QuickSight and security features supported per model
10. How to load data into QuickSight and how to refresh data
11. When to use Glue and where to use EMR. Know the limitations of Glue
12. S3 store tiers and lifecycle policies
13. Data transformations/conversions – Kinesis Firehose, Lambda, Kinesis Data Analytics, Glue
14. Data formats that improve data processing e.g. Avro, ORC, Parquet
15. Take the exam readiness course from AWS to assess your readiness
Services to know for the exam
- Glue & Glue Data Catalog
- S3
- DynamoDB
- Kinesis Data Streams
- Kinesis Firehose
- Redshift and Spectrum
- EMR and Hadoop Ecosystem
- Lambda
- Athena
- Quicksight
- Kinesis Data Analytics
- ElasticSearch and Kibana
- RDS & Aurora
- Amazon MSK
- IOT Core
- Data Pipeline
- DMS
- Snowball and Direct Connect
- SageMaker
- Security considerations for all above services
Resources Used
Certification Preparation course
AWS Free Digital Courses
- Exam Readiness: AWS Certified Data Analytics – Specialty
- Best Practices for Data Warehousing with Amazon Redshift
Practice Test
White Papers
- Big Data Analytics Options on AWS
- Lambda Architecture for Batch and Stream Processing
- Use Amazon ES to Log and Monitor Almost Everything
- Streaming Data Solutions on AWS with Amazon Kinesis
Keep learning and Good Luck on your exam!
Author: Emmanuel Koomson is a Product Owner, Solution Architect, 9X AWS Certified and a life long learner. You can connect with him on LinkedIn.
More from the author: How to Prepare for AWS Certified Database Specialty