Learn Matillion ETL integrating with AWS Redshift
What you'll learn Matillion ETL
Matillion ETL Data Integration Process
Cloud Data Integration
Redshift Integration
Requirements No programming experience required. Good to have basic ETL knowledge
Description Modern cloud-native ETL platform Matillion extracts your data, loads it into your cloud data warehouse (CDW), then uses the power and flexibility of your CDW or Delta Lake to transform your data into meaningful business insights.Matillion ETL is an ETL/ELT tool built specifically for cloud database platforms including Amazon Redshift, Google BigQuery, Snowflake and Azure Synapse. It is a modern, browser-based UI, with powerful, push-down ETL/ELT functionality. With a fast setup, you are up and running in minutes.Unlocks the power of your data warehouse: Matillion ETL pushes down data transformations to your data warehouse. Process millions of rows in seconds, with real-time feedback.Modern, beautiful, browser-based environment: including collaboration, version control, full-featured graphical job development, and more than 20 data read, write, join, and transform components.Fast setup: Launch and be developing ETL jobs within minutes.To get started with Matillion ETL, you will need to decide which version and instance type of Matillion ETL is best for you. The instance type you select affects the maximum number of concurrent users who can access Matillion ETL and the maximum number of environments you can connect to.Once you have launched Matillion ETL, you should be able to connect and start creating workflows in minutes
Overview
Section 1: Introduction
Lecture 1 What will you Learn?
Lecture 2 Matillion - Navigating through the Console and Properties
Lecture 3 Configuring Matillion ETL instance in AWS
Lecture 4 Creating First Job in Matillion
Section 2: Working with Read & Write Components
Lecture 5 Fixed Flow
Lecture 6 Multi Table Input
Lecture 7 Table Delete Row
Lecture 8 Table Update - Delete/Insert
Lecture 9 Table Update - Update/Insert
Lecture 10 Rewrite Table
Lecture 11 Create View
Section 3: Transform
Lecture 12 Calculator
Lecture 13 Aggregate
Lecture 14 Detect Changes
Lecture 15 Distinct
Lecture 16 Filter
Lecture 17 First/Last
Lecture 18 Lead/Lag
Lecture 19 Map Values
Lecture 20 Rank
Lecture 21 Rename
Lecture 22 Replicate
Lecture 23 Sql
Lecture 24 Transpose Row
Section 4: Join
Lecture 25 Except
Lecture 26 Intersect
Lecture 27 Join
Lecture 28 Join Multiple
Lecture 29 Self Join - Method1
Lecture 30 Self Join - Method2
Lecture 31 Cartesian Join
Lecture 32 Unite
Section 5: Orchestration
Lecture 33 Overview
Lecture 34 Orchestration Job
ETL Developers,ETL Architects,Data Integration Specialists,Cloud Data Engineers,Data Engineers,Data Warehouse Developers
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