Data Warehousing on AWS Training (DWAWS) course with Hands-on Labs
Data Warehousing on AWS Training (DWAWS) course introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS.
This Data Warehousing on AWS Training (DWAWS) course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis Firehose, and Amazon S3. Additionally, this Data Warehousing on AWS Training course demonstrates how to use business intelligence tools to perform analysis on your data.
Duration: 3 days
- AWS Technical Essentials Training (AWSE)
- Architecting on AWS Training (AWSA)
- Advanced Architecting on AWS Training (AWSAA)
- Migrating to AWS Training (AWSM)
- Microsoft Azure for AWS Experts (40390)
- Systems Operations on AWS Training (AWSSYS)
- DevOps Engineering on AWS Training (AWSDEVOPS)
- Developing on AWS Training (AWS-DEV)
- Big Data on AWS Training (BDAWS)
- Data Warehousing on AWS Training (DWAWS)
- Security Engineering on AWS Training (AWSSO)
- AWS Business Essentials Training (AWSBE)
• If you are familiar with some aspects of this Data Warehousing on AWS Training (DWAWS) course, we can omit or shorten their discussion.
• We can adjust the emphasis placed on the various topics or build the Data Warehousing on AWS Training (DWAWS) course around the mix of technologies of interest to you (including technologies other than those included in this outline).
• If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policy-maker), and present the Data Warehousing on AWS Training (DWAWS) course in manner understandable to lay audiences.
Audience / Target Group:
The target audience for this Data Warehousing on AWS Training (DWAWS) course:
• Database Architects
• Database Administrators
• Database Developers
• Data Analysts and Scientists
The knowledge and skills that a learner must have before attending this Data Warehousing on AWS Training (DWAWS) course are as follows:
• AWS Technical Essentials (AWSE)
• Familiarity with relational databases and database design concepts
Upon completing this Data Warehousing on AWS Training (DWAWS) course, learners will be able to meet these objectives:
• Discuss the core concepts of data warehousing.
• Evaluate the relationship between Amazon Redshift and other big data systems.
• Evaluate use cases for data warehousing workloads and review case studies that demonstrate implementation of AWS data and analytic services as part of a data warehousing solution.
• Choose an appropriate Amazon Redshift node type and size for your data needs.
• Discuss security features as they pertain to Amazon Redshift, such as encryption, IAM permissions, and database permissions.
• Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud.
• Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis Firehose, and Amazon S3, to contribute to the data warehousing solution.
• Evaluate approaches and methodologies for designing data warehouses.
• Identify data sources and assess requirements that affect the data warehouse design.
• Design the data warehouse to make effective use of compression, data distribution, and sort methods.
• Load and unload data and perform data maintenance tasks.
• Write queries and evaluate query plans to optimize query performance.
• Configure the database to allocate resources such as memory to query queues and define criteria to route certain types of queries to your configured query queues for improved processing.
• Use features and services, such as Amazon Redshift database audit logging, Amazon CloudTrail, Amazon CloudWatch, and Amazon Simple Notification Service (Amazon SNS), to audit, monitor, and receive event notifications about activities in the data warehouse.
• Prepare for operational tasks, such as resizing Amazon Redshift clusters and using snapshots to back up and restore clusters.
• Use a business intelligence (BI) application to perform data analysis and visualization tasks against your data.
Data Warehousing on AWS Training (DWAWS) – Course Syllabus:
• Course Introduction
• Introduction to Data Warehousing
• Introduction to Amazon Redshift
• Understanding Amazon Redshift Components and Resources
• Launching an Amazon Redshift Cluster
• Reviewing Data Warehousing Approaches
• Identifying Data Sources and Requirements
• Designing the Data Warehouse
• Loading Data into the Data Warehouse
• Writing Queries and Tuning Performance
• Maintaining the Data Warehouse
• Analyzing and Visualizing Data
• Course Summary
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