Course Description
In this course, professionals will develop a data analytics solution utilizing Amazon Redshift, a cloud data warehouse service. The course concentrates on the data collection, ingestion, cataloging, storage, & processing components of the analytics pipeline. Professionals will learn to integrate Amazon Redshift with a data lake to support both analytics & machine learning workloads. Professionals will also learn to apply security, performance, & cost management ideal practices to the operation of Amazon Redshift.
Prerequisites
Students with a minimum of one year of experience managing data warehouses will benefit from this course.
We recommend that attendees of this course have-
- Completed either AWS Technical Essentials or Architecting on AWS
- Completed Building Data Lakes on AWS
Target Audience
This course is intended for data warehouse engineers, data platform engineers, & architects & operators who build & manage data analytics pipelines.
Course Objectives
In this course, you will learn to-
- Compare the features & benefits of data warehouses, data lakes, & modern data architectures
- Design & implement a data warehouse analytics solution
- Identify & apply appropriate techniques, including compression, to optimize data storage
- Select & deploy appropriate options to ingest, transform, & store data
- Choose the appropriate instance & node types, clusters, auto-scaling, & network topology for a
- particular business use case
- Understand how data storage & processing affect the analysis & visualization mechanisms
- needed to gain actionable business insights
- Secure data at rest & in transit
- Monitor analytics workloads to identify & remediate problems
- Apply cost management best practices
Content Outline
- Data analytics use cases
- Using the data pipeline for analytics
- Why Amazon Redshift for data warehousing?
- Overview of Amazon Redshift
- Amazon Redshift architecture
- Interactive Demo 1- Touring the Amazon Redshift console
- Amazon Redshift features
- Practice Lab 1- Load & query data in an Amazon Redshift cluster
- Ingestion
- Interactive Demo 2- Connecting your Amazon Redshift cluster using a Jupyter notebook with
- Data API
- Data distribution & storage
- Interactive Demo 3- Analyzing semi-structured data using the SUPER data type
- Querying data in Amazon Redshift
- Practice Lab 2- Data analytics using Amazon Redshift Spectrum
- Data transformation
- Advanced querying
- Practice Lab 3- Data transformation & querying in Amazon Redshift
- Resource management
- Interactive Demo 4- Applying mixed workload management on Amazon Redshift
- Automation & Optimization
- Interactive demo 5- Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster
- Securing the Amazon Redshift cluster
- Monitoring & troubleshooting Amazon Redshift clusters
- Data warehouse use case review
- Activity- Designing a data warehouse analytics workflow
Modern data architecture
FAQs
Amazon Redshift is a fully managed service & offers both provisioned & serverless options, making it more efficient for you to run & scale analytics without having to handle your data warehouse. One can turn up a fresh Amazon Redshift Serverless endpoint to automatically provision the data warehouse in seconds or choose the given option for predictable workloads.
EC2 is a service that enables business clients to run application programs in the computing environment.
TPC-DS benchmark results exhibit that Amazon Redshift provides the ideal price performance, even for a small 3 TB dataset. Amazon Redshift offers up to 5x better price implementation than other cloud data warehouses. You can gain from Amazon Redshift’s leading price performance from the start without manual tuning. Based on our performance fleet telemetry, we know that most workloads are short query workloads (that run in less than 1 second). For these workloads, the latest benchmarks exhibit that Amazon Redshift offers up to 7x more reasonable price performance on heightened concurrency and low dormancy workloads than any other cloud data warehouses.
Radiant believes in a practical & creative approach to training & development, which distinguishes it from other activity & developmental platforms. Moreover, training courses are undertaken by some experts with a vast range of experience in their domain.
Radiant team of experts will be available at e-mail support@radianttechlearning.com to answer your technical queries after the training program.
Yes, Radiant will provide you with the most updated, high, valuable & relevant real-time projects & case studies in each training program.
Technical issues are unpredictable & might occur with us as well. Participants must ensure access to the required configuration with good internet speed.
Radiant Techlearning offers training programs on weekdays, weekends & combination of weekdays & weekends. We provide you with complete liberty to choose the schedule that suits your needs.