Data Warehousing on AWS
You will be introduced to concepts, strategies and best practices for designing cloud-based data warehousing solutions using Amazon RedShift. The course also teaches you how to collect, store and analyze data for the data warehouse by using AWS services.
- Live Demonstrations
- Group Discussions
- Frequent Knowledge Checks
- Hands-On Labs
- Database Architects
- Database Administrators
- Database Developers
- Data Analysts
- Data Scientists
- Taken AWS Technical Essentials (or equivalent experience with AWS)
- Knowledge of relational databases and database design concepts
Module 1: Introduction to Data Warehousing
- Relational databases
- Data warehousing concepts
- The intersection of data warehousing and big data
- Overview of data management in AWS
- Hands-on lab 1: Introduction to Amazon Redshift
Module 2: Introduction to Amazon Redshift
- Conceptual overview
- Real-world use cases
- Hands-on lab 2: Launching an Amazon Redshift cluster
Module 3: Launching clusters
- Building the cluster
- Connecting to the cluster
- Controlling access
- Database security
- Load data
- Hands-on lab 3: Optimizing database schemas
Module 4: Designing the database schema
- Schemas and data types
- Columnar compression
- Data distribution styles
- Data sorting methods
Module 5: Identifying data sources
- Data sources overview
- Amazon S3
- Amazon DynamoDB
- Amazon EMR
- Amazon Kinesis Data Firehose
- AWS Lambda Database Loader for Amazon Redshift
- Hands-on lab 4: Loading real-time data into an Amazon Redshift database
Module 6: Loading data
- Preparing Data
- Loading data using COPY
- Maintaining tables
- Concurrent write operations
- Troubleshooting load issues
- Hands-on lab 5: Loading data with the COPY command
Module 7: Writing queries and tuning for performance
- Amazon Redshift SQL
- User-Defined Functions (UDFs)
- Factors that affect query performance
- The EXPLAIN command and query plans
- Workload Management (WLM)
- Hands-on lab 6: Configuring workload management
Module 8: Amazon Redshift Spectrum
- Amazon Redshift Spectrum
- Configuring data for Amazon Redshift Spectrum
- Amazon Redshift Spectrum Queries
- Hands-on lab 7: Using Amazon Redshift Spectrum
Module 9: Maintaining clusters
- Audit logging
- Performance monitoring
- Events and notifications
- Lab 8: Auditing and monitoring clusters
- Resizing clusters
- Backing up and restoring clusters
- Resource tagging and limits and constraints
- Hands-on lab 9: Backing up, restoring and resizing clusters
Module 10: Analyzing and visualizing data
- Power of visualizations
- Building dashboards
- Amazon QuickSight editions and features
Class Deliverables
- Amazon Authorised Instructors
- Official AWS Content
- Hands-on labs (*where available)
- Class completion certificates
- Exam Prep sessions
Dates Available - Click on Book Now to proceed
| Virtual | 3 days | All Day | October 8, 2024 | ₹0 | |
| Virtual | 3 days | All Day | October 22, 2024 | ₹0 | |
| Virtual | 3 days | All Day | November 5, 2024 | ₹0 | |
| Virtual | 3 days | All Day | November 19, 2024 | ₹0 | |
| Virtual | 3 days | All Day | December 3, 2024 | ₹0 | |
| Virtual | 3 days | All Day | December 17, 2024 | ₹0 |
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FAQs
To enroll in this course, choose the starting date and make an online payment. Once your payment is confirmed, our team will reach out to you.
Wire Transfer, Credit Card, Debit Card, UPI & Purchase Order.
There is no minimum number of candidates required, we are happy to train 1 to 1 . With regards to the maximum number, we can accomodate 30 learners in one batch.
- Training Delivered by an Amazon Authorized Instructor.
- AWS Content E-Kit
- Hands-on-labs for 30 days
- Class attendance certificate
You will get the access to course content & lab on first day of your training session.
The course Completion Certificate will be issued to your email id within 2 weeks of completing your course.
A one-day course could be delivered over two half day sessions (4 hours a day), or a three-day course could be delivered over five days (4 hours a day)
