This course includes:
- 2 practice tests
- Full lifetime access
- Access on mobile
[March 2022 Updated]: Latest exam questions added.
Get Ready To Prepare Like You’ve Never Prepared Before!!!
If you are preparing for DAS-C01 or AWS Certified Data Analytics– Specialty Associate certification and looking for guidance and resources then you have come to the right place.
Finally! Pass AWS Certified Data Analytics– Specialty (DAS-C01) Exam in just 3 days with a 100% money-back guarantee.
Preparing for your Certified AWS Certified Data Analytics– Specialty (DAS-C01) certification, assess your knowledge of topics on the exam with these practice test questions.
The purpose of this Practice Question Set is to help you pass the Certified AWS Certified Data Analytics– Specialty exam. These practice questions will make you very familiar with both the type and the difficulty level of the questions on the (DAS-C01) certification test. This practice exam gives you the feeling of reality and is a clue to the questions asked in the actual certification exam.
The AWS Certified Data Analytics – Specialty exam validates individuals who have the in depth skills required to build, deploy, and tune data models and leverage AWS services to streamline this process at scale. Take this intermediate-level course to learn how to prepare for the exam by exploring the exam’s topic areas and how they map to data analysis on AWS and to specific areas to study.
We’ve crafted this course to give you the knowledge and technique to pass the DAS-C01 exam in the first time. The practice tests include this topics:
- Navigate the logistics of the examination process
- Understand the exam structure and question types
- Identify how questions relate to AWS data analytics concepts
- Interpret the concepts being tested by exam questions
- And much more
Best of luck!
· Type : multiple choice or multiple response
· Duration : 180 Minutes
· Number of Questions : 65
· Passing score : 70%
Who this course is for:
- Data platform engineers
- Data architects
- Data scientists
- Data analysts
- Solutions architects
- IT Professionals