Data Warehousing on AWS
- Offered byKnowledgeHut
Data Warehousing on AWS at KnowledgeHut Overview
Duration | 3 days |
Start from | Start Now |
Total fee | ₹39,945 |
Mode of learning | Online |
Official Website | Go to Website  |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
- Admission Process
Data Warehousing on AWS at KnowledgeHut Highlights
- Earn a certificate after completion of course
- Fee can be paid in installments
Data Warehousing on AWS at KnowledgeHut Course details
Data architects
Database administrators
Database developers
Data analysts
Data scientists
Gain a thorough understanding of data warehousing concepts and discover the elements of big data solutions
Evaluate case studies and review real-world AWS data implementation as a part of data warehousing solutions
Use AWS analytic and data services like Amazon EMR, Amazon Kinesis, Amazon S3 and a lot more
Get hands-on experience in identifying data sources and loading real-time data into Amazon Redshift database
Identify performance issues and optimize queries accordingly to facilitate a high-performing database
Perform data analysis and visualize tasks with the help of advanced tools such as Amazon QuickSight
KnowledgeHut is an AWS Training Partner (ATP) and our instructor-led Data Warehousing on AWS training specialty course is taught by top Amazon Certified Trainers with considerable industry experience
The course helps you thrive in your career in data science, helping you implement the right strategies, use the right tools to seamlessly build Data Warehousing solutions on AWS
You will also learn to leverage Amazon QuickSight for data analysis and visualization
Class Schedule
09:00 AM - 01:00 PM(Weekend)
Data Warehousing on AWS at KnowledgeHut Curriculum
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
2. Introduction to Amazon Redshift
Conceptual overview
Real-world use cases
Hands-on lab 2: Launching an Amazon Redshift cluster
3. Launching Clusters
Building the cluster
Connecting to the cluster
Controlling access
Database security
Load data
Hands-on lab 3: Optimizing database schemas
4. Designing the Database Schema
Schemas and data types
Columnar compression
Data distribution styles
Data sorting methods
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
6. Loading Data
Preparing Data
Loading data using COPY
Data Warehousing on AWS at KnowledgeHut Admission Process
Important Dates
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