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    Data Warehousing on AWS - 3 Days Instructor-Led Training

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    Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS.
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    Data Warehousing on AWS - 3 Days Instructor-Led Training

     Info

    Overview

    Course Overview

    This course demonstrates how to collect, store, and prepare data for the data warehouse by using AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data.

    Start your AWS Databases journey by accessing Official AWS e-Learning for FREE. Learn Amazon Aurora Service Introduction, Introduction to Amazon DynamoDB, Amazon Redshift Service Introduction and more - GET STARTED 

    Level: Intermediate

    Duration: 3 Days

    Delivery Type: Instructor-Led Training

    Course Objectives

    • Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions
    • Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud
    • Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution
    • Architect the data warehouse
    • Identify performance issues, optimize queries, and tune the database for better performance
    • Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket
    • Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse

    Prerequisites

    Required

    • Familiarity with relational databases and database design concepts

    Who Should Go For This Training?

    • Database Architects
    • Database Administrators
    • Database Developers
    • Data Analysts and Scientists

    Course Outline

    Day 1

    Module 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

    Module 2: Introduction to Amazon Redshift

    • Conceptual overview
    • Real-world use cases
    • Hands-on lab 2: Launching an Amazon Redshift cluster

    Module 3: Launching clusters

    • Building the cluster
    • Connecting to the cluster
    • Controlling access
    • Database security
    • Load data
    • Hands-on lab 3: Optimizing database schemas

    Day 2

    Module 4: Designing the database schema

    • Schemas and data types
    • Columnar compression
    • Data distribution styles
    • Data sorting methods

    Module 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

    Module 6: Loading data

    • Preparing Data
    • Loading data using COPY
    • Maintaining tables
    • Concurrent write operations
    • Troubleshooting load issues
    • Hands-on lab 5: Loading data with the COPY command

    Day 3

    Module 7: Writing queries and tuning for performance

    • Amazon Redshift SQL
    • User-Defined Functions (UDFs)
    • Factors that affect query performance
    • The EXPLAIN command and query plans
    • Workload Management (WLM)
    • Hands-on lab 6: Configuring workload management

    Module 8: Amazon Redshift Spectrum

    • Amazon Redshift Spectrum
    • Configuring data for Amazon Redshift Spectrum
    • Amazon Redshift Spectrum Queries
    • Hands-on lab 7: Using Amazon Redshift Spectrum

    Module 9: Maintaining clusters

    • Audit logging
    • Performance monitoring
    • Events and notifications
    • Lab 8: Auditing and monitoring clusters
    • Resizing clusters
    • Backing up and restoring clusters
    • Resource tagging and limits and constraints
    • Hands-on lab 9: Backing up, restoring and resizing clusters

    Module 10: Analyzing and visualizing data

    • Power of visualizations
    • Building dashboards
    • Amazon QuickSight editions and features

    Highlights

    • Data Warehousing on AWS training leads to AWS Certified Database - Specialty Certification.

    Details

    Delivery method

    Pricing

    Custom pricing options

    Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.

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    Support

    Vendor support

    To learn more about our AWS trainings please visit NetCom Learning  or do not hesitate to contact our Sales Team: aws@netcomlearning.com  | (888)563-8266