AWS certification > AWS Certified Data Engineer Associate
AWS Certified Data
AWS Certified Data
Engineer - Associate
| Category | Associate |
|---|---|
| Exam duration | 130 minutes |
| Exam format | 65 questions; either multiple choice or multiple response |
| Cost | 150 USD. Visit Exam pricing for additional cost information, including foreign exchange rates |
| Testing options | Pearson VUE testing center or online proctored exam |
| Languages offered | English, Japanese, Korean, and Simplified Chinese |
The AWS Certified Data Engineer - Associate validates skills and knowledge in core data-related AWS services, ability to ingest and transform data, orchestrate data pipelines while applying programming concepts, design data models, manage data life cycles, and ensure data quality.
Course Details
1. Perform data ingestion
- Throughput and latency characteristics for AWS services that ingest data
- Data ingestion patterns (for example, frequency and data history)
- Streaming data ingestion
- Batch data ingestion (for example, scheduled ingestion, event-driven ingestion)
- Replay ability of data ingestion pipelines
- Stateful and stateless data transactions
2. Transform and process data.
- Creation of ETL pipelines based on business requirements
- Volume, velocity, and variety of data (for example, structured data, unstructured data)
- Cloud computing and distributed computing
- How to use Apache Spark to process data
- Intermediate data staging locations
3. Orchestrate Data Pipelines
- How to integrate various AWS services to create ETL pipelines
- Event-driven architecture
- How to configure AWS services for data pipelines based on schedules or dependencies
- Implementing and maintaining Serverless workflows
- Using notification services to send alerts (for example, Amazon Simple Notification Service [Amazon SNS], Amazon Simple Queue Service [Amazon SQS])
4. Apply Programming Concepts
- Continuous integration and continuous delivery (CI/CD) (implementation, testing, and deployment of data pipelines)
- SQL queries (for data source queries and data transformations)
- Infrastructure as code (IaC) for repeatable deployments (for example, AWS Cloud Development Kit [AWS CDK], AWS CloudFormation)
- Distributed computing
- Data structures and algorithms (for example, graph data structures and tree data structures)
- SQL query optimization
5. Choose a data store
- Storage platforms and their characteristics
- Storage services and configurations for specific performance demands
- Data storage formats (for example, .csv, .txt, Parquet)
- How to align data storage with data migration requirements
- How to determine the appropriate storage solution for specific access patterns
- How to manage locks to prevent access to data (for example, Amazon Redshift, Amazon RDS)
6. Understand data cataloguing systems
- How to create a data catalog
- Data classification based on requirements
- Components of metadata and data catalogs
7. Manage the lifecycle of data
- Appropriate storage solutions to address hot and cold data requirements
- How to optimize the cost of storage based on the data lifecycle
- How to delete data to meet business and legal requirements
- Data retention policies and archiving strategies
- How to protect data with appropriate resiliency and availability
8. Design data models and schema evolution
- Data modelling concepts
- How to ensure accuracy and trustworthiness of data by using data lineage
- Best practices for indexing, partitioning strategies, compression, and other data optimization techniques
- How to model structured, semi-structured, and unstructured data
- Schema evolution techniques
9. Automate data processing by using AWS services
- How to maintain and troubleshoot data processing for repeatable business outcomes
- API calls for data processing
- Which services accept scripting (for example, Amazon EMR, Amazon Redshift, AWS Glue)
10. Analyse data by using AWS services
- Tradeoffs between provisioned services and serverless services
- SQL queries (for example, SELECT statements with multiple qualifiers or JOIN clauses)
- How to visualize data for analysis
- When and how to apply cleansing techniques
- Data aggregation, rolling average, grouping, and pivoting
11. Maintain and monitor data pipelines
- How to log application data
- Best practices for performance tuning
- How to log access to AWS services
- Amazon Macie, AWS CloudTrail, and Amazon CloudWatch
12. Ensure data quality
- Data sampling techniques
- How to implement data skew mechanisms
- Data validation (data completeness, consistency, accuracy, and integrity)
- Data profiling
13. Apply authentication mechanisms
- VPC security networking concepts
- Differences between managed services and unmanaged services
- Authentication methods (password-based, certificate-based, and role-based)
- Differences between AWS managed policies and customer managed policies
14. Apply authorization mechanisms
- Authorization methods (role-based, policy-based, tag-based, and attribute-based)
- Principle of least privilege as it applies to AWS security
- Role-based access control and expected access patterns
- Methods to protect data from unauthorized access across services
15. Ensure Data Encryption and masking
- Data encryption options available in AWS analytics services (for example, Amazon Redshift, Amazon EMR, AWS Glue)
- Differences between client-side encryption and server-side encryption
- Protection of sensitive data
- Data anonymization, masking, and key salting
16. Prepare logs for audit
- How to log application data
- How to log access to AWS services
- Centralized AWS logs
17. Understand data privacy and governance
- How to protect personally identifiable information (PII)
- Data sovereignty
| Fees Structure : | 12500 INR / 150 USD |
| Total No of Class : | 74 Video Class |
| Class Duration : | 38:30 Working Hours |
| Download Feature : | Download Avalable |
| Technical Support : | Call / Whatsapp : +91 8680961847 |
| Working Hours : | Monday to Firday 9 AM to 6 PM |
| Payment Mode : | Credit Card / Debit Card / NetBanking / Wallet (Gpay/Phonepay/Paytm/WhatsApp Pay) |
| Fees Structure : | 22500 INR / 270 USD |
| Class Duration : | 45 Days |
| Class Recording : | Live Class Recording available |
| Class Time : | Monday to Firday 1.5 hours per day / Weekend 3 Hours per day |
| Technical Support : | Call / Whatsapp : +91 8680961847 |
| Working Hours : | Monday to Firday 9 AM to 6 PM |
| Payment Mode : | Credit Card / Debit Card / NetBanking / Wallet (Gpay/Phonepay/Paytm/WhatsApp Pay) |
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