Amazon Redshift Demystified
Amazon Redshift Demystified
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Beginner
5( 92 Reviews )
4 Hrs
Cloud Security
Beginner5(92 Reviews)4 HrsBuilding a Resilient and Secure Data Warehouse using Amazon’s DWH As A Service
Building a Resilient and Secure Data Warehouse using Amazon’s DWH As A Service
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7 Quizzes & Assessments
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Overview
Data is the new oil.
Data is becoming the science and the art of making insightful decisions for every organization from healthcare, sciences, agriculture, financial services, telecommunications, and political decisions.
The data is in the details and all the decision that you have to make is based on the patterns that emerge in the data that you collect and all this begins with setting up your Analytical Massively Parallel Processing (MPP) Databases with Amazon Redshift that is already optimized for managing analytical workloads.
In this course, you will learn how to build a data warehouse using Amazon’s Data Warehouse As A Service (Redshift). More importantly, you will learn the difference between OLTP (Online Transaction Processing systems) and OLAP (Online Analytical Processing Systems).
You will also learn how to build clusters of 2 or more nodes of Massively Parallel Processing Data Warehouse systems and load data from multiple databases into your Amazon Redshift Cluster.
You will also manage the data and generate analysis, without compromising the security of your data and system of records, while running on one of the most cloud systems in the world.
What You Will Learn
Analyze and Discuss the core concepts of data warehousing- Understand the relationship between Amazon Redshift and other big data systems
- Implement data warehousing use cases and review case studies that demonstrate implementation of AWS data warehousing solutions
- Size your Amazon Redshift node type to meet your present and future data requirements
- Review security features that exists on Amazon Redshift, such as IAM permissions, encryption and database permissions
- Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud
- Review various approaches and methodologies used for designing data warehouses
- Identify data sources and assess requirements that affect the data warehouse design
- Design the warehouse to make 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
- Prepare for operational tasks, such as resizing Amazon Redshift clusters and using snapshots to back up and restore clusters
Prerequisites
- Knowledge of relational databases and database design concepts
- Knowledge of cloud computing concepts
- A computer system with the following OS: Windows or iOS-based system, Processor: 1.8 GHz, Memory: 8 GB, Access to Amazon Web Services (You must log on to Amazon and create an Account)
Course Content
Chapter 1: Introduction to Redshift and Cluster Management in Redshift
3 Videos | 0 hrs 13 mins
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Chapter 2: Architectural Overview of Redshift Internals
4 Videos | 0 hrs 24 mins
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Chapter 3: Data Warehouse Design Considerations using Redshift
4 Videos | 0 hrs 35 mins
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Chapter 4: Loading Data into Redshift
7 Videos | 1 hr 4 mins
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Chapter 5: Securing Your Redshift Data
4 Videos | 0 hrs 39 mins
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Chapter 6: Backup and Recovery of Redshift Data
3 Videos | 0 hrs 26 mins
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Chapter 7: Performance Tuning of Redshift
2 Videos | 0 hrs 19 mins
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Chapter 8: Key Takeaways from the Course
2 Videos | 0 hrs 9 mins
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Instructor
Michael Onuorah
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Learn moreReviews
5
92 reviews
Average Course Rating
5 stars
51%4 stars
48%3 stars
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