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Data List Management
Microsoft Office Excel Level 4
Spreadsheet Analysis
Microsoft Office Excel Level 5 VBA Macros
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Microsoft Office Powerpoint Level 1
Microsoft Office Powerpoint Level 2
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Microsoft Office Outlook Level 2
AWS Data Analytics
Course Outlines
Domain 1: Collection
1.1 Determine the operational characteristics of the collection system
1.2 Select a collection system that handles the frequency of data change and type of data being ingested
1.3 Identify the properties that need to be enforced by the collection system: order, data structure,
metadata, etc.
1.4 Explain the durability and availability characteristics for the collection approach
Domain 2: Storage
2.1 Determine and optimize the operational characteristics of the storage solution
2.2 Determine data access and retrieval patterns
2.3 Evaluate mechanisms for capture, update, and retrieval of catalog entries
2.4 Determine appropriate data structure and storage format
Domain 3: Processing
3.1 Identify the appropriate data processing technology for a given scenario
3.2 Determine how to design and architect the data processing solution
3.3 Determine the operational characteristics of the solution implemented
Domain 4: Analysis
4.1 Determine the tools and techniques required for analysis
4.2 Determine how to design and architect the analytical solution
4.3 Determine and optimize the operational characteristics of the Analysis
Domain 5: Visualization
5.1 Determine the appropriate techniques for delivering the results/output
5.2 Determine how to design and create the Visualization platform
5.3 Determine and optimize the operational characteristics of the Visualization system
Domain 6: Data Security
6.1 Determine encryption requirements and/or implementation technologies
6.2 Choose the appropriate technology to enforce data governance
6.3 Identify how to ensure data integrity
6.4 Evaluate regulatory requirements
What you'll learn
- Move and transform massive data streams with Kinesis
- Store big data with S3 and DynamoDB in a scalable, secure manner
- Process big data with AWS Lambda and Glue ETL
- Use the Hadoop ecosystem with AWS using Elastic MapReduce
- Apply machine learning to massive data sets with Amazon ML, SageMaker, and deep learning
- Analyze big data with Kinesis Analytics, Amazon Elasticsearch Service, Redshift, RDS, and Aurora
- Visualize big data in the cloud using AWS QuickSight
Course Content
- Move and transform massive data streams with Kinesis
- Store big data with S3 and DynamoDB in a scalable, secure manner
- Process big data with AWS Lambda and Glue ETL
- Use the Hadoop ecosystem with AWS using Elastic MapReduce
- Apply machine learning to massive data sets with Amazon ML, SageMaker, and deep learning
- Analyze big data with Kinesis Analytics, Amazon Elasticsearch Service, Redshift, RDS, and Aurora
- Visualize big data in the cloud using AWS QuickSight
Customize a Course
We will be happy to assist you for inquiries about a customized scheduled or program:
Rachael McPherson, Director of Sales
☎(250)882-9549 📧[email protected]
Caroline Santos, Corporate and Custom Sales Manager- Eastern Canada
☎(514)771-3206 📧[email protected]
