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Learn Matillion Etl - Cloud Native Data Integration Platform

LeeAndro

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Trusted Editor
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Published 6/2022MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 1.49 GB | Duration: 3h 1m

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 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- 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 Eeers,Data Eeers,Data Warehouse Developers

HomePage:
Code:
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