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Jamie Fry

From beginner to Competent user in just one concise course. This course teaches you ALL the functionality of Tableau Prep.

The three stages of this course:

  1.  First Steps

Getting the must know basics out the way quickly

  1.  Creating Data Flows

Teaches you the functionality of Tableau Prep, enabling you to use all of Tableau Preps functionality

  1.  Project

An interesting assignment to test your learning. Followed by detailed review.

Read more

From beginner to Competent user in just one concise course. This course teaches you ALL the functionality of Tableau Prep.

The three stages of this course:

  1.  First Steps

Getting the must know basics out the way quickly

  1.  Creating Data Flows

Teaches you the functionality of Tableau Prep, enabling you to use all of Tableau Preps functionality

  1.  Project

An interesting assignment to test your learning. Followed by detailed review.

Tableau Desktop Knowledge is preferred but not essential. I advise people to learn desktop first before attempting to use Tableau Prep (for context).

Why a course by Jamie Fry?

I have 10 years experience with tableau products in the workplace. I've watched it grow from simple drag and drop tool into a extremely powerful visualisation software, from a Private company to an IPO. I am not a full time udemy instructor, which i believe is a strength. What i will teach you i use everyday in my workplace, for all different manner of clients across the globe. My technical teaching of this tool comes with real workplace Do's and Don'ts, teaching you will not get from full time instructors that have been out of the workplace for a number of years. I teach tableau in classrooms face to face and via video conferencing, and years of this experience has led to this streamlined course. Please see my Bio for more information on my academic and professional background.

For details on the precise functionality taught, Please see the 'Curriculum For This Course' below.

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What's inside

Learning objective

Understand fully and have practical experience using 'tableau prep'

Syllabus

Introduction

Please view lectures in 1080p!

Please view in 1080p!

Understand what Tableau Prep does, the problem it solves. When it should and shouldn't be used. How it fits with other tableau products..

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Understand how the course is structured and what you will learn

Links and advice to installing Tableau Prep

What workspaces there are in the Tableau Prep workspace and what they are used for.

Understand the basics of data preparation principles; data reduction, cleaning, integration, transformation.

Understand how to connect to different data sources and connect to our first data table

Understand what the input step is

Understand what the profile pane is and its uses

Learn how to clean data in the flow using a clean step. Rename fields, split data, change data types, filter, clean punctuation, change alias.

Learn to group and replace multiple values using fuzzy matching algorithms

Learn how to output your data, and the different files types

Learn how to reshape data in the flow using pivot and calculated fields

Learn how to aggregate data in flow

Learn the two different options to do a union, wildcard and union step

Learn how to join data in the flow

Understand the project task and tips for completing it

Step by step review of the project output. If downloading the titanic workbook, please change file extension to twbx (udemy doesnt allow .twbx extensions to be uploaded, hence why i changed to pdf)

Wrap up and what next. How to get your certificate: https://support.udemy.com/hc/en-us/articles/229603868-Certificate-of-Completion

Understand what you need to address when introducing tableau into an enterprise (business) environment

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Reading list

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Shows you how to use Tableau Prep to prepare your data for data visualization. It covers the basics of Tableau Prep and provides practical tips on how to use the tool to get the most out of your data.
Provides a comprehensive overview of Tableau Prep, covering all the essential concepts and techniques you need to get started with data preparation. It's perfect for beginners who want to learn the basics of Tableau Prep.
Provides a collection of tips and tricks for using Tableau Prep. It's a great resource for users who want to learn how to use Tableau Prep more efficiently.
Provides a step-by-step guide to Tableau Prep, covering all the essential concepts and techniques you need to get started with data preparation. It's a great resource for beginners who want to learn the basics of Tableau Prep.
Focuses on data preparation for Spark. It covers a wide range of topics, including data cleaning, data integration, and data transformation. It valuable resource for data engineers and other professionals who work with Spark.
Provides a comprehensive overview of data preparation techniques for big data. It covers a wide range of topics, including data cleaning, data integration, and data transformation. It valuable resource for data engineers, data scientists, and other professionals who work with big data.
Focuses on data preparation for computer vision. It covers a wide range of topics, including data cleaning, data augmentation, and data transformation. It valuable resource for data scientists and other professionals who work with computer vision.
Considered a classic in the field of statistical learning and data mining, this book covers various techniques that often require significant data preparation. While mathematically rigorous, it provides foundational knowledge on concepts like feature engineering and data transformation. It is more suitable for graduate students and researchers with a strong mathematical background.
Focuses on data preparation for business intelligence. It covers a wide range of topics, including data cleaning, data integration, and data transformation. It valuable resource for business intelligence professionals and other professionals who work with data.
Focuses on data preparation for Hadoop. It covers a wide range of topics, including data cleaning, data integration, and data transformation. It valuable resource for data engineers and other professionals who work with Hadoop.
While not solely focused on data preparation, this book provides essential context by explaining the overall data-analytic thinking process and where data preparation fits in. It helps readers understand the business value of data and the importance of quality data for effective analysis and decision-making.
This book, written by the creator of the pandas library, practical introduction to the tools needed for data manipulation, cleaning, and preparation in Python. It is highly relevant for anyone working with data in Python and serves as an excellent resource for both beginners and those looking to solidify their understanding of using pandas and NumPy for data preparation tasks. is widely used and considered a standard reference in the field.
An excellent resource for those using R, this book provides a comprehensive introduction to data wrangling, transformation, and visualization using the tidyverse suite of packages. It fundamental text for anyone learning data science with R, covering essential data preparation steps. is often used as a textbook in introductory data science courses.
Offers a broader perspective on data wrangling principles beyond specific tools. It delves into the process and techniques for preparing data effectively, regardless of the software or language used. It's valuable for gaining a solid understanding of the underlying concepts of data preparation. This book is suitable for both students and professionals seeking a deeper understanding of data wrangling methodologies.
Focuses on practical data preprocessing specifically for machine learning applications using popular Python libraries like scikit-learn and pandas. It's highly relevant for those preparing data for modeling and provides hands-on examples. This book is particularly useful for students and professionals in the machine learning domain.
This handbook takes a pragmatic approach to dealing with messy, real-world data. It provides a collection of techniques and war stories for handling various data quality issues. It valuable resource for practitioners who encounter challenging data problems regularly and offers practical solutions and insights.
Focuses on data preparation for data mining. It covers a wide range of topics, including data cleaning, data integration, and data transformation. It valuable resource for data miners and other professionals who work with data mining.
Offers a comprehensive view of the data engineering landscape, which includes data preparation as a crucial component. It covers the entire data lifecycle and provides a strong foundation for understanding how data is generated, ingested, transformed, and stored. This book is highly relevant for those interested in the broader aspects of data infrastructure and would be valuable for graduate students and working professionals in data engineering roles.
Focuses on data preparation for exploratory data analysis. It covers a wide range of topics, including data cleaning, data visualization, and data transformation. It valuable resource for data analysts and other professionals who work with data.
Focuses on data preparation for machine learning. It covers a wide range of topics, including data cleaning, feature engineering, and data transformation. It valuable resource for data scientists and other professionals who work with machine learning.

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