AWS Certified Data Analytics – Specialty Exam Study Guide
The AWS Certified Data Analytics – Specialty exam is intended for people who have experience in designing, building, securing, and maintaining analytics solutions on AWS. The exam will test your technical skills on how different AWS analytics services integrate with each other. You also need to know how they fit in the data lifecycle of collection, storage, processing, and visualization.
This specialty certification exam is on par with the other AWS Professional level tests so you need to allocate ample time for your preparation. With the help of the official exam study guide, you can determine the areas that you need to focus on. It will show you the specific knowledge areas and domains that you must review to pass the exam.
Before taking the actual exam, we recommend checking out these study materials for AWS Certified Data Analytics Specialty. These resources will help you understand the concepts and strategies that you will need for you to pass the exam.
- Free Exam Readiness: AWS Certified Data Analytics – Specialty – this is an interactive course that has responsive image maps, accordions, sample problem sets, section-based quizzes, and a practice test in the end.
- AWS FAQs – can help you grasp every service briefly. The responses you will find here are commonly asked questions, use cases, and comparison of various AWS services.
- Tutorials Dojo’s AWS Cheat Sheets – can help you understand the lengthy concepts found in the AWS FAQs. These cheat sheets are presented in a bullet point format to help you digest the information easily. This page summarizes all the analytics services of AWS.
- AWS Knowledge Center – you can use this website to find and understand the most frequent questions and requests AWS receives from its customers.
- AWS Documentation and Whitepapers – this document will help you expand your knowledge on various AWS services with its detailed information. You can focus on the following whitepapers:
- Amazon EMR Migration Guide: How to Move Apache Spark and Apache Hadoop From On-Premises to AWS
- Big Data Options on AWS
- Lambda Architecture for Batch and Stream Processing
- Streaming Data Solutions on AWS with Amazon Kinesis
- Teaching Big Data Skills with Amazon EMR
- Reference Architecture: SQL Based Data Processing in Amazon ECS
- Tutorials Dojo’s AWS Certified Data Analytics Specialty Practice Exams (coming soon!) – this provides a comprehensive reviewer with complete and detailed explanations to help you pass your AWS Data Analytics exam on your first try. The Tutorials Dojo practice exams are well-regarded as the best AWS practice test reviewers in the market.
AWS Services to Focus On
The AWS Certified Data Analytics Specialty has five domains: Collection, Storage and Data Management, Processing, Analysis and Visualization, and Security. To comprehend the different scenarios in the exam, you should have a thorough understanding of the following services:
- Amazon Athena – learn how you can analyze the data in the S3 bucket and how you can configure and optimize Athena’s performance.
- Amazon CloudSearch – know the use case and features of the service.
- Amazon Elasticsearch – learn how you can integrate Elasticsearch and Kibana in different AWS services.
- Amazon EMR – understand the security, hardware, and software configurations of the EMR cluster and how you can use AWS Glue Data Catalog for table metadata.
- Amazon Kinesis – know the use case of each Kinesis service (Data Streams, Data Firehose, and Data Analytics) and how they differ from each other.
- Amazon QuickSight – learn how you can integrate QuickSight into your solution, how you can publish dashboards, reports, analytics, and how you can refresh your datasets.
- Amazon Redshift – understand the different SQL commands, the use case of Redshift cluster, Redshift Spectrum, and how you can analyze the data in the data warehouse.
- AWS Data Pipeline – learn the concepts and components of the pipeline.
- AWS Glue – understand the concepts of the data catalog, crawlers, workflows, triggers, jobs, job bookmarks, and job metrics.
You must know how these services interact to develop a complete data analytics solution in AWS. Also, prepare to see various Apache technologies, such as Apache Parquet, ORC, Avro, Oozie, Sqooq, HBase, and many more.
Validate Your Knowledge
After you’ve reviewed the materials above, the next resource that you should check is the FREE AWS sample questions for AWS Data Analytics Specialty. Although this sample exam is not on the same level of difficulty as one might expect on the real exam, it is still a helpful resource for your review. Be sure to check the sample questionnaire often since AWS may upload a new version of it.
For high-quality practice exams, you can use our AWS Certified Data Analytics Specialty practice exams (coming soon!). These practice exams will help you boost your preparedness for the real exam. It contains multiple sets of questions that cover almost every area that you can expect from the real certification exam. We have also included detailed explanations and adequate reference links to help you understand why the option with the correct answer is better than the rest of the options. This is the value that you will get from our course. Practice exams are a great way to determine which areas you are weak in, and it will also highlight the important information that you might have missed during your review.
To understand a service at a higher level, we recommend that you get hands-on experience. A lot of questions in the exam try to validate whether you’ve seen a particular error or issue during your practice. To prepare yourself for the actual exam, you can use the AWS Free Tier account to simulate different scenarios. With the combination of theoretical and practical knowledge, you can pass the test with flying colors.
We hope that our guide has helped you achieve your goal, and we would love to hear back from you after your exam. Remember that the most important thing before the day of your exam is to get some well-deserved rest. Good luck, and we wish you all the best.