A tanfolyamról
Understand the central idea behind a data warehouse and how data warehousing fits in the larger context of big data solutions. Get expert guidance on using the AWS suite of services like Amazon EMR, Amazon Kinesis, Amazon DynamoDB, and Amazon S3 for all aspects of data collection, preparation, processing, storage, and optimization for better performance.
The 24 hours instructor-led Data Warehousing on AWS training 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.
Who Should Attend the Course
- Data architects
- Database administrators
- Database developers
- Data analysts
- Data scientists
What You Will Learn
-
Concepts of Data Warehousing
Gain a thorough understanding of data warehousing concepts and discover the elements of big data solutions -
Evaluate Data & Analytics
Evaluate case studies and review real-world AWS data implementation as a part of data warehousing solutions -
Leverage AWS Services
Use AWS analytic and data services like Amazon EMR, Amazon Kinesis, Amazon S3 and a lot more -
Identify Data Sources
Get hands-on experience in identifying data sources and loading real-time data into Amazon Redshift database -
Ensure Enhanced Performance
Learn to identify performance issues and optimize queries accordingly to facilitate a high-performing database -
Perform Data Analysis
Perform data analysis and visualize tasks with the help of advanced tools such as Amazon QuickSight
This course comes with a comprehensive curriculum and expert-led sessions that will help you to learn:
- Core concepts of Data Warehousing
- Use advanced tools like Amazon QuickSight for Data Analysis
- Use advanced data services such as Amazon Kinesis, Amazon EMR, and more
- Load real-time data into Amazon Redshift
- And a lot more...
We provide this course in English.
Tematika
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
Kinek ajánljuk
Előfeltételek
Prerequisites
- Familiarity with relational databases
- Knowledge of database design concepts