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)

Data Structure

Tableau is optimized for use with data in a tabular (table-based) structure. This is a structure that you may be familiar with through working with Microsoft Excel or similar software. Vertical columns store values for whatever the column (or field) represents, such as an item description or order date; horizontally, each row of values collectively forms a record (which can be thought of as an observation).

For example, a company may record transactions across its stores in a table such as Table 1.1 (sampled to the first transaction – 000001 – in store number 677):

Store Code

Transaction ID

Item Code

Quantity

Purchase DateTime

677

000001

0000145-GRY

10

2024-01-03 09:15:32

677

000001

0000096-AAA

5

2024-01-03 09:16:01

677

000001

0000452-BLU

2

2024-01-03 09:16:23

Table 1.1: Example of a tabular structure

As each record represents an item bought, it is apparent that three distinct products were bought as part of this single transaction. Each key data point relating to these records (such as quantity, purchase date, or time) is stored neatly in a distinct column.

Relational databases such as Microsoft SQL Server and many common file types have this tabular structure as a default, or at least a simple alternative structure (such as comma-separated values) that Tableau can quickly convert into a table as it loads the data.