AWS Certified Data Analytics - Specialty
- Product Code: das-c01
- Exam Questions: 150
- Vendor: amazon
$9.99
$12.99- Updated At: Nov 14, 2024
AWS Certified Data Analytics - Specialty
The AWS Certified Data Analytics - Specialty certification is designed for data analysts and professionals who work with data lakes, data warehousing, and big data analytics.
Focus
The AWS Certified Data Analytics - Specialty certification focuses on Data analytics and science
Exam Duration
The AWS Certified Data Analytics - Specialty exam duration is 170 minutes
Num of Question
The exam contains a total of 85
Exam Fee
The exam fee is $300.
Exam Validity
The CCRN-Pediatric certification is valid for 3 years.
Prior Certification
- Experience with AWS and data analytics
Exam Format
The AWS Certified Data Analytics - Specialty exam is a Multiple-choice and multiple-response questions
Passing Conditions
To pass AWS Certified Data Analytics - Specialty exam, applicants must achieve a minimum score of 66% (passing score 57 out of 85 questions)
Who Should Take
Data analysts, data scientists, business analysts, and anyone working with data analytics in a cloud environment.
- Data Analyst
- Data Scientist
- Business Analyst
Prerequisites
3+ years of experience in a data analytics role and 1+ year of experience in an AWS environment (recommended).
Or can substitute with certifications:
- AWS Certified Developer - Associate
- AWS Certified Solutions Architect - Associate
Certification Process
- Step 1: Meet the prerequisites and prepare for the exam
- Step 2: Register for the exam and schedule a test time
- Step 3: Take the exam and pass the required percentage
- Step 4: Obtain the certification and maintain it for 3 years
Domains with Weights
- Data Lake Architecture (20%): This domain evaluates your ability to design and implement a data lake architecture that supports analytics workloads, such as Amazon S3, Amazon S3 Lake Formation, and Amazon Redshift.
- Data Warehousing and Data Mart (20%): This domain evaluates your ability to design and implement data warehousing and data mart solutions that support analytics workloads, such as Amazon Redshift, Amazon QuickSight, and Amazon QuickSight.
- Data Engineering for Analytics (20%): This domain evaluates your ability to engineer data pipelines, data workflows, and data architectures that support analytics workloads, such as Apache Spark, Amazon Glue, and Amazon Kinesis.
- Big Data Analytics (15%): This domain evaluates your ability to design and implement big data analytics solutions that support various data sources, such as Apache Hadoop, Apache Hive, and Amazon Elastic MapReduce (EMR).
- Data Science and Engineering (25%): This domain evaluates your ability to design and implement data science and engineering solutions that support various data sources, such as machine learning algorithms, data visualizations, and data modeling.
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