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We're here to help you find itUnlock the full potential of AWS with our Data Processing and Orchestration on AWS course. Over just 2 days (16 hours), gain a deep understanding of Data pipelines, orchestration, and key AWS services for efficient data processing. From Data ingestion and Storage to processing and Visualization, you'll follow a step-by-step approach that emphasizes Best practices for security, Cost optimization, and disaster recovery. Practical labs, like Incremental data load from S3 to Redshift and Creating a data lake with Lake Formation, ensure hands-on learning. This course suits those looking to master data workflows using AWS Glue, Step Functions, and CloudWatch, among others.
Successfully delivered 2 sessions for over 2 professionals
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USD
View Fees Breakdown
| Course Fee | 850 |
|
Total Fees |
850 (USD) |
♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
To successfully undertake the Data Processing and Orchestration on AWS course, students should have the following minimum prerequisites:
These prerequisites are designed to ensure that learners can grasp the course content effectively, yet are broad enough to encourage wide participation. Don't worry if you are not proficient in all these areas; the course is structured to help you build practical skills progressively.
Brief Introduction about the Course:
Koenig Solutions' Data Processing and Orchestration on AWS course prepares IT professionals to adeptly manage data pipelines, orchestration, and AWS services for end-to-end data processing.
Job Roles and Audience for the Course:
The Data Processing and Orchestration on AWS course offers an in-depth understanding of data pipelines, orchestration, and relevant AWS services. It equips students with the skills needed for data ingestion, storage, processing, visualization, and best practices, all in a span of 16 hours over 2 days.
