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Introduce Amazon DAS-C01 Exam
Do you want to validate expertise in using AWS data lakes and analytics services to get insights from data? Then you can choose to complete the AWS Certified Data Analytics – Specialty certification to prove that you can identify and develop talent with critical skills for implementing cloud initiatives. You need to take the DAS-C01 exam to complete the certification.
DAS-C01 Exam Overview
- Level: Specialty
- Test Time: 180 Minutes
- Exam Questions: 65
- Delivery Method: Pearson VUE testing center or online proctored exam
- Languages: English, Japanese, Korean, and Simplified Chinese.
- Required Skills: A minimum of 5 years of experience with common data analytics technologies; at least 2 years of hands-on experience and expertise
working with AWS services to design, build, secure, and maintain analytics solutions.
Learning DAS-C01 Exam Objectives Is Strongly Recommended
- Determine the operational characteristics of the collection system
- Select a collection system that handles the frequency, volume, and the source of data
- Select a collection system that addresses the key properties of data, such as order, format, and compression
- Determine the operational characteristics of the storage solution for analytics
- Determine data access and retrieval patterns
- Select appropriate data layout, schema, structure, and format
- Define data lifecycle based on usage patterns and business requirements
- Determine the appropriate system for cataloging data and managing metadata
- Determine appropriate data processing solution requirements
- Design a solution for transforming and preparing data for analysis
- Automate and operationalize data processing solutions
- Determine the operational characteristics of the analysis and visualization solution
- Select the appropriate data analysis solution for a given scenario
- Select the appropriate data visualization solution for a given scenario
- Select appropriate authentication and authorization mechanisms
- Apply data protection and encryption techniques
- Apply data governance and compliance controls
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