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Data Integration, Data Preparation and Exploratory Data Analysis all in one tool

What you will learn

Learn how to clean, transform and analyse data

Data Integration

Exploratory Data Analysis

Trifacta Wrangler basics

Description

So much time in Data Science, Analytics or Analysis activities is spent preparing data, approximately 50-80 percent!

The need for efficiency and capabilities in terms of data integration, preparation and transformation is understandably at an all time high.

That’s where Trifacta Wrangler comes into play with its extensive capabilities in Extracting, Transforming and Loading (ETL) data.

This course is for absolute beginners and will cover the basics to get you started.

We will be using a movie ratings dataset and introduce some real world style requirements so you can get hands on experience.


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In this course you will:

  • Set up a free trial of Trifacta cloud
  • Learn the basics of Trifacta, its ecosystem and the interface
  • Understand Trifacta terminology such as Recipes and Flows
  • Ingest raw data and output clean, transformed data as per real world requirements
  • Understand how to collaborate and share flows

In just one hour you will go from absolute beginner to being able to integrate data from multiple sources, perform data preparation and cleansing to raw data sets, exploratory data analysis and more.

About me

As your instructor I am a professional Data Consultant and have over 10 years of on the job experience working for both private and public experience.

I have over 100,000 students enrolled in my courses worldwide and all of my courses have an average rating of over 4.5

English
language

Content

Introduction and Set Up

Course Introduction
What is Trifacta?
Setting up Your Trial Account
Interface Overview
Dataset Download

Transforming your Data

Creating your first “Flow”
The Transformer View
Formatting Data
Supported Data Types (External Link)
Introduction to Functions
Trifacta Functions (External Link)
Filtering Records
Working with Dates
Splitting and Extracting Data
Text and Pattern Matching (External Links)
Adding a Conditional Column
Pivot and Unpivot
Unions
Joins
Lookup
Grouping your Data

Jobs and Collaborating

Running Outputs and Scheduling your Flow
Sharing and Collaborating