Building Data Analytics Solutions Using Amazon Redshift
In this course, you will build a Data Analytics solution using Amazon Redshift, a cloud data warehouse service. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads.
The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift.
This course is intended for Data Warehouse Engineers, Data platform engineers, Architects and operators who build and manage data analytics pipelines.
This course includes presentations, interactive demos, practice labs, discussions, and class exercises
1 Day / 8 Hours
Live Class
Certificate on completion
Objectives
This AWS course will include the following activities
- Group Discussions
- Live Demonstrations
- Presentations
- Hands-On Labs
- Knowledge Checks
Prerequisites
To qualify for taking up this course, you’ll need the following:
- Completed either AWS Technical Essentials or Architecting on AWS
- Completed Building Data Lakes on AWS
Intended Audience
You can take on this course if you belong to the following category of individuals:
- Data warehouse engineers, data platform engineers, architects, and operators who create and oversee data analytics pipelines are the target audience for this course.
Activities
This AWS course will include the following activities:
- Group Discussions
- Live Demonstrations
- Presentations
- Hands-On Labs
- Knowledge Checks
Module A: Overview of Data Analytics and the Data Pipeline
Data analytics use cases
Using the data pipeline for analytics
Module 1: Using Amazon Redshift in the Data Analytics Pipeline
Why Amazon Redshift for data warehousing?
Overview of Amazon Redshift
Module 2: Introduction to Amazon Redshift
Amazon Redshift architecture
Interactive Demo 1: Touring the Amazon Redshift console
Amazon Redshift features
Practice Lab 1: Load and query data in an Amazon Redshift cluster
Module 3: Ingestion and Storage
Ingestion
Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API
Data distribution and 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
Module 4: Processing and Optimizing Data
Data transformation
Advanced querying
Practice Lab 3: Data transformation and querying in Amazon Redshift
Resource management
Interactive Demo 4: Applying mixed workload management on Amazon Redshift
Automation and optimization
Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster
Module 5: Security and Monitoring of Amazon Redshift Clusters
Securing the Amazon Redshift cluster
Monitoring and troubleshooting Amazon Redshift clusters
Module 6: Designing Data Warehouse Analytics Solutions
Data warehouse use case review
Activity: Designing a data warehouse analytics workflow
Module B: Developing Modern Data Architectures on AWS
Modern data architectures
Talk to a Learning Advisor
Exam Readiness
AWS Certified Data Analytics - Specialty
Certification
AWS Certified Data Analytics - Specialty
FAQs
Yes, we are an AWS Advanced Tier Training Partner
Anyone who wants to start a profession in AWS cloud is fit to enroll in this course. No prior knowledge of coding or other technical skills is required.
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.
You may reach out at the contact number listed on our official website or write to us at info@cloudwizard.wpenginepowered.com.
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 should you wish. With regard to the maximum number, we can accommodate 30 learners in one batch.
1. Training delivered by an Amazon Authorised Instructor
2. AWS Content E-Kit
3. Hands-on labs- 30 days
4. 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).
MOBILE LAYOUT
Building Data Analytics Solutions Using Amazon Redshift
1 Day / 8 Hours
Live Class
Certificate on completion
Objectives
This AWS course will include the following activities
- Group Discussions
- Live Demonstrations
- Presentations
- Hands-On Labs
- Knowledge Checks
Prerequisites
To qualify for taking up this course, you’ll need the following:
- Completed either AWS Technical Essentials or Architecting on AWS
- Completed Building Data Lakes on AWS