Experience expert-led training delivered privately to your team either at your location or in an interactive virtual classroom. Our On-Site/Private Training options—including Virtual Team Training—is both cost-effective and convenient for your team of six or more. Get a no-obligation quote and details about how easy it is to give your team a private training experience. Call our Learning & Coaching Advocates at 929.777.8102, or email [email protected].
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Data Warehousing on AWS
Designed for database architects, administrators, developers, data analysts and scientists, and more, this 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.
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Description
Learn how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data. This course teaches you how to:
- Discuss the core concepts of data warehousing.
- Discuss the intersection between data warehousing and big data solutions.
- 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, and Amazon S3, to contribute to the data warehousing solution.
- Evaluate approaches and methodologies for designing data warehouses.
- Identify data sources and determine requirements for accessing the data.
- Architect the data warehouse.
- Use important commands, such as COPY, UNLOAD, and VACUUM, to manage the data in the data warehouse.
- Identify performance issues, optimize queries, and tune the database for better performance
- Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket.
- Use features and services, such as Amazon Redshift database auditing, Amazon CloudWatch, Amazon CloudTrail, and Amazon Simple Notification Service (Amazon SNS), to monitor and audit the data warehouse.
- Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse.
Who Should Attend?
This course is intended for:
- Database architects
- Database administrators
- Database developers
- Data analysts and scientists
Prerequisites
We recommend that attendees of this course have the following prerequisites:
- Courses taken: AWS Technical Essentials (or equivalent experience with AWS)
- Familiarity with relational databases and database design concepts
Delivery Method
This course will be delivered through a mix of:
- Instructor-led Training
- Hands on Lab Exercises
Hands-On Activity
This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.
Questions? 929.777.8102 [email protected]
Course Outline
Day 1
- Course Introduction
- Introduction to Data Warehousing
- Introduction to Amazon Redshift
- Understanding Amazon Redshift Components and Resources
- Launching an Amazon Redshift Cluster
Day 2
- Choosing a Data Warehousing Approach
- Identifying Data Sources and Requirements
- Architecting the Data Warehouse
- Loading Data into the Data Warehouse
Day 3
- Optimizing Queries and Tuning Performance
- Monitoring and Auditing the Data Warehouse
- Maintaining the Data Warehouse
- Analyzing and Visualizing Data
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Don't see a date that fits your schedule? Contact us for scheduling options at 929.777.8102
Course Duration: 3 Days
Description
Learn how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data. This course teaches you how to:
- Discuss the core concepts of data warehousing.
- Discuss the intersection between data warehousing and big data solutions.
- 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, and Amazon S3, to contribute to the data warehousing solution.
- Evaluate approaches and methodologies for designing data warehouses.
- Identify data sources and determine requirements for accessing the data.
- Architect the data warehouse.
- Use important commands, such as COPY, UNLOAD, and VACUUM, to manage the data in the data warehouse.
- Identify performance issues, optimize queries, and tune the database for better performance
- Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket.
- Use features and services, such as Amazon Redshift database auditing, Amazon CloudWatch, Amazon CloudTrail, and Amazon Simple Notification Service (Amazon SNS), to monitor and audit the data warehouse.
- Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse.
Who Should Attend?
This course is intended for:
- Database architects
- Database administrators
- Database developers
- Data analysts and scientists
Prerequisites
We recommend that attendees of this course have the following prerequisites:
- Courses taken: AWS Technical Essentials (or equivalent experience with AWS)
- Familiarity with relational databases and database design concepts
Delivery Method
This course will be delivered through a mix of:
- Instructor-led Training
- Hands on Lab Exercises
Hands-On Activity
This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.
Questions? 929.777.8102 [email protected]
Course Outline
Day 1
- Course Introduction
- Introduction to Data Warehousing
- Introduction to Amazon Redshift
- Understanding Amazon Redshift Components and Resources
- Launching an Amazon Redshift Cluster
Day 2
- Choosing a Data Warehousing Approach
- Identifying Data Sources and Requirements
- Architecting the Data Warehouse
- Loading Data into the Data Warehouse
Day 3
- Optimizing Queries and Tuning Performance
- Monitoring and Auditing the Data Warehouse
- Maintaining the Data Warehouse
- Analyzing and Visualizing Data
Bring this course to your team at your site. Contact us to learn more at 929.777.8102.
Dates
Mode
Location
Price
Course Duration: 3 Days
Ways to Save
Save on Private Training for Your Team
Experience expert-led training delivered privately to your team either at your location or in an interactive virtual classroom. Our On-Site/Private Training options—including Virtual Team Training—is both cost-effective and convenient for your team of six or more. Get a no-obligation quote and details about how easy it is to give your team a private training experience. Call our Learning & Coaching Advocates at 929.777.8102, or email [email protected].
Description
Learn how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data. This course teaches you how to:
- Discuss the core concepts of data warehousing.
- Discuss the intersection between data warehousing and big data solutions.
- 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, and Amazon S3, to contribute to the data warehousing solution.
- Evaluate approaches and methodologies for designing data warehouses.
- Identify data sources and determine requirements for accessing the data.
- Architect the data warehouse.
- Use important commands, such as COPY, UNLOAD, and VACUUM, to manage the data in the data warehouse.
- Identify performance issues, optimize queries, and tune the database for better performance
- Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket.
- Use features and services, such as Amazon Redshift database auditing, Amazon CloudWatch, Amazon CloudTrail, and Amazon Simple Notification Service (Amazon SNS), to monitor and audit the data warehouse.
- Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse.
Who Should Attend?
This course is intended for:
- Database architects
- Database administrators
- Database developers
- Data analysts and scientists
Prerequisites
We recommend that attendees of this course have the following prerequisites:
- Courses taken: AWS Technical Essentials (or equivalent experience with AWS)
- Familiarity with relational databases and database design concepts
Delivery Method
This course will be delivered through a mix of:
- Instructor-led Training
- Hands on Lab Exercises
Hands-On Activity
This course allows you to test new skills and apply knowledge to your working environment through a variety of practical exercises.
Questions? 929.777.8102 [email protected]
Course Outline
Day 1
- Course Introduction
- Introduction to Data Warehousing
- Introduction to Amazon Redshift
- Understanding Amazon Redshift Components and Resources
- Launching an Amazon Redshift Cluster
Day 2
- Choosing a Data Warehousing Approach
- Identifying Data Sources and Requirements
- Architecting the Data Warehouse
- Loading Data into the Data Warehouse
Day 3
- Optimizing Queries and Tuning Performance
- Monitoring and Auditing the Data Warehouse
- Maintaining the Data Warehouse
- Analyzing and Visualizing Data
Questions?
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