Book Image

Tableau Certified Data Analyst Certification Guide

By : Mr. Harry Cooney, Mr. Daisy Jones
Book Image

Tableau Certified Data Analyst Certification Guide

By: Mr. Harry Cooney, Mr. Daisy Jones

Overview of this book

The Tableau Certified Data Analyst certification validates the essential skills needed to explore, analyze, and present data, propelling your career in data analytics. Whether you're a seasoned Tableau user or just starting out, this comprehensive resource is your roadmap to mastering Tableau and achieving certification success. The book begins by exploring the fundamentals of data analysis, from connecting to various data sources to transforming and cleaning data for meaningful insights. With practical exercises and realistic mock exams, you'll gain hands-on experience that reinforces your understanding of Tableau concepts and prepares you for the challenges of the certification exam. As you progress, expert guidance and clear explanations make it easy to navigate complex topics as each chapter builds upon the last, providing a seamless learning experience—from creating impactful visualizations to managing content on Tableau Cloud. Written by a team of experts, this Tableau book not only helps you pass the certification exam but also equips you with the skills and confidence needed to excel in your career. It is an indispensable resource for unlocking the full potential of Tableau.
Table of Contents (11 chapters)

Cleaning Data

This section will walk you through the Tableau Desktop and Tableau Prep cleaning functionalities, starting with what is important when assessing data quality. Cleaning in Tableau Desktop will be followed by using the data interpreter, using folders to organize data sources, and finally, cleaning in Tableau Prep.

Cleaning data refers to either removing unwanted data or fixing broken data. This can include processes such as removing duplicates and outliers or fixing incorrect values and formatting. For example, an invoice system may produce a data source with duplicate invoice records in error. For the data source to be usable in Tableau, the duplicate records would have to be removed to ensure that invoices are not double counted, resulting in inflated totals.

Ensuring data is clean before analysis is a key step, as the results of the analysis can only be trusted once the data source is confirmed as accurate and reliable. Every data source is different in terms of...