Tableau Certified Data Analyst Certification Guide E-Book

Harry Cooney

• Herausgeber: Packt Publishing
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 504

Veröffentlichungsjahr: 2024

Beschreibung

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.

Leseprobe

Tableau Certified Data Analyst Certification Guide

Ace the Tableau Data Analyst certification exam with expert guidance and practice material

Harry Cooney

Daisy Jones

Tableau Certified Data Analyst Certification Guide

Copyright © 2024 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Authors: Harry Cooney and Daisy Jones

Reviewers: Jess Hancock and Mahendra Singh

Publishing Product Manager: Sneha Shinde

Senior-Development Editor:Ketan Giri

Development Editor:Kalyani S.

Presentation Designer: Salma Patel

Editorial Board: Vijin Boricha, Megan Carlisle, Simon Cox, Ketan Giri, Saurabh Kadave, Alex Mazonowicz, Gandhali Raut, and Ankita Thakur

First Published: June 2024

Production Reference: 1240624

Published by Packt Publishing Ltd.

Grosvenor House

11 St Paul’s Square

Birmingham

B3 1RB

ISBN: 978-1-80324-346-7

www.packtpub.com

Contributors

About the Authors

Harry Cooney, is a Senior Data Consultant who has worked with Tableau for the past five years, transforming business questions into analytical dashboards that enable users to generate insights about their business as well as mentoring Tableau users of all skill levels, both individually and through corporate training. In addition to this professional experience, Harry has even had his Tableau work featured in the Tableau Conference Virtual Gallery and made the shortlist for the 2023 World Data Visualization Prize.

Outside of work, Harry is a fan of football and enjoys incorporating this interest into Tableau by creating reports to compare team and player stats.

LinkedIn profile: https://www.linkedin.com/in/harrycooney/

Daisy Jones is a Senior Data Consultant and Chief Party Officer at The Information Lab Ireland. After completing a degree in Chinese Studies, Daisy discovered The Information Lab Ireland’s training program where she gained the skills in Tableau and Alteryx that would spark a passion for creative design with Tableau dashboards. Four years later, she is now working with clients to help them utilize best data practices and create data driven answers for their business.

Away from the office, Daisy is normally found in the gym, crocheting, or playing computer games.

LinkedIn profile: https://www.linkedin.com/in/daisy-jones1995/

About the Reviewers

Jess Hancock has worked closely with a range of clients across the finance, aerospace, higher education, and non-profit sectors. For Jess, there's nothing more satisfying than bridging the gap between developers and decision-makers to turn raw data into useful information.

In her spare time, Jess enjoys painting, birdwatching, and being out in nature.

LinkedIn profile: https://www.linkedin.com/in/jess-h/

Mahendra Singh is a seasoned data analyst, consultant, and data scientist with over 10 years of experience in the industry. He has been using Tableau Desktop and Server applications for seven years and has worked with several large-scale US firms to build and maintain Tableau visuals and installations. Mahendra completed his Bachelor's degree in Information Technology with a focus on Software Development in 2015. He has worked in various industries, including healthcare, food and beverage, and banking and finance. Mahendra's areas of expertise and interest include business intelligence, big data and analytics, Spark, and machine learning.

Table of Contents

Preface

1

Connecting to Data

Introduction to Data

Making the Most Out of This Book – Your Certification and Beyond

Connecting to Sources

Data Structure

Choosing an Appropriate Data Source Type

Content and Quality

Level of detail: Dimensions and Measures

Data Quality

Technical Requirements

Performance: Data Size and Structure

Microsoft Excel (.xlsx) and Comma-Separated Values (.csv) Types

Relational Databases

Initial Data Connections

Connecting to Tableau Server or Tableau Cloud

Connecting to a File

CSV and Excel Files

.hyper or .tde Files

JSON

PDF

Spatial Files

Statistical Files

Connecting to Databases and Cloud Services

Default Server Connectors

Custom SQL Queries

Introduction to SQL and Custom Queries in Tableau

Live versus Extract Connections

Live Connections

Data Extracts

Other Factors Affecting Performance

Connection Management: the Datasource Pane and Data Tab

The Datasource Window

The Data Tab

Making New Connections in Existing Workbooks

Replacing Data Sources

Notes, Caveats, and Unsupported Data Sources

Web-Based Data Access: Drivers and APIs

Multidimensional Systems

Summary

Exam Readiness Drill – Chapter Review Questions

2

Transforming Data

Introduction

Types of Fields in Tableau

Data Types

Data Type Conversion

Dimensions and Measures

Dimensions and Measure Field Conversion

Discrete and Continuous

Dimension, Measure, Discrete, and Continuous Combinations

Discrete and Continuous Color Legends

Cleaning Data

Assessing Data Quality

Cleaning data on Tableau Desktop

Duplicating and Renaming a Field Updating the Aliases

Updating the Default Properties of Fields

Data Interpreter

Using Data Interpreter in Tableau Desktop

Organizing the Data Source

Creating a Folder

Cleaning Data in Tableau Prep

Using Tableau Prep’s Data Cleaning Functionality

Transforming Data

Tableau Desktop Transformations

Splitting a Field in Tableau Desktop

Pivoting Fields in Tableau Desktop

Aggregating Data in Tableau Prep

Aggregating Data

Pivoting Data in Tableau Prep

Pivoting Rows to Columns in Tableau Prep

Pivoting Columns to Rows in Tableau Prep

Combining Data

Tableau Desktop Joins

Creating a Join in Tableau Desktop

Tableau Desktop Unions

Creating a Union in Tableau Desktop

Relationships

Creating a Relationship in Tableau Desktop

Blending

Creating a Blend Relationship in Tableau

Primary versus Secondary Data Source Choice

Tableau Prep Joins

Creating a Join in Tableau Prep

Tableau Prep Unions

Creating a Union in Tableau Prep

Summary

Exam Readiness Drill – Chapter Review Questions

3

Calculations

Introduction

Defining Calculations

Calculated Fields

Aggregated Calculated Fields

Measure Aggregation

Using the SUM and MIN Functions

Math Functions

Using the MEDIAN and STDEV Functions

Fixed Level of Detail Calculations

Creating a Fixed Level of Detail Calculation

Numeric Calculated Fields

Transformational Mathematical Functions

Using the SQUARE and SQRT Functions

Field Format Functions

Using the ROUND and ABS Functions

Trigonometry

Using the SIN and RADIANS Functions

String Calculated Fields

Positional Functions

Using the RIGHT, LEFT, and MID Functions

Searching

Using the CONTAINS, STARTSWITH, and REPLACE Functions

Case

Using the UPPER and LOWER Functions

Other

Using the SPLIT and LEN Functions

Date Calculated Fields

Date Parts

Using the YEAR, MONTH, DAY, and DATEPART Functions

Date Logic

Using the DATETRUNC and DATEADD Functions

Using the DATEDIFF and TODAY Functions

Type Conversion

Data Types

Using the STR and MAKEDATE Functions

Boolean Calculated Fields

Boolean Functions

Using the IN Function

IF Logic

Using the IIF Function and Creating an IF Statement

CASE Statements

Writing a CASE Statement

Table Calculations

Building a Table Calculation

Moving Calculations

Percent of Total

Running Sum

Difference and Percent of Difference

Percentile

Custom Table Calculations

INDEX

Rank

First-and Last

Summary

Exam Readiness Drill – Chapter Review Questions

4

Grouping and Filtering

Introduction

Data Grouping

Sets

Creating a Fixed Set and Filtering Data

Creating a Top N Set

Creating a Conditional Set

Combining Sets for Advanced Analysis

Groups

Creating a Group from Data Points in a View

Editing the Group

Hierarchies

Creating a Product Hierarchy

Using a Hierarchy in a View

Bins

Creating a Sales Bin and Counting the Customers in Each

Filtering

Types of Filters

Filtering Directly from the View

Filter Configuration

Creating a Wildcard Filter

Creating a Conditional Filter

Creating a Top N Filter

Creating a Date Filter

Creating a Table Calculation Filter

Applying Filters to Single or Multiple Sheets

Applying a Filter to Multiple Worksheets

Filtering and the Order of Operations

Creating a Data Source Filter

Context Filtering Exercise

Parameters

Parameter Creation

Creating a String Parameter from an Existing Field

Creating an Integer Parameter

Creating a Date Parameter

Parameters in Calculated Fields

Using a Parameter in a Calculated Field

Filtering with Parameters

Filtering with a Parameter

Customizing Reference Lines Using Parameters

Customizing a Reference Line Using a Parameter

Summary

Exam Readiness Drill – Chapter Review Questions

5

Charts

Introduction

Area Chart

Bar Chart

Box Plot

Bullet Graph

Heatmap

Gantt Chart

Highlight Table

Histogram Table

Line Chart

Packed Bubble Chart

Pie Chart

Scatter Plot

Text Table

Treemap

Combination Chart

Geographic Charts

Symbol Maps

Creating a Symbol Map in Tableau

Density/Heat Maps

Creating a Density Map in Tableau

Filled Maps

Creating a Filled Map in Tableau

Analytics

Totals and Subtotals

Creating Totals and Subtotals

Reference Lines and Average Lines

Creating a Constant and Average Reference Line in Tableau

Reference Bands and Distribution Bands

Creating a Reference Band and a Distribution Band

Box Plots

Creating a Box Plot

Trend Lines

Adding a Trend Line to a Chart in Tableau

Forecasting

Creating and Customizing a Forecast in Tableau

Predictive Models

Creating a Predictive Model in Tableau

Summary

Exam Readiness Drill – Chapter Review Questions

6

Dashboards

Introduction

Dashboard Creation

Dashboard Objects

Sheets

Containers

Text

Image

Blank

Buttons

Web Page

Extensions

Ask Data

Data Story

Workflow

Creating a Dashboard and Adding a Sheet and a Title

Adding a Container and Another Sheet to the Dashboard

Adding Buttons to the Dashboard

Layout Options

Dashboard Sizing/Device Layouts

Floating versus Tiled

Adding Tiled Objects and Floating Objects to a Dashboard

Resizing the Default Canvas and Updating the Phone Layout

Dashboard Interactivity

Dashboard Actions

Filter Actions

Highlight Actions

URL actions

Adding Filter Actions to the Dashboard

Adding a Highlight Action to the Dashboard

Adding a URL Action to the Dashboard

Adding User-Guiding Sentences to Improve the End-User Experience

Filtering Multiple Sheets

Adding a Filter to the Dashboard and Applying it to All Sheets

Sheet Swapping

Creating a Sheet Swapper and Applying it to the Dashboard

Dashboard Best Practices

Stories

Creating a Story

Summary

Exam Readiness Drill – Chapter Review Questions

7

Formatting

Introduction

Applying Color, Font, Shapes, and Styling

Color

Font

Alignment

Tooltips

Shapes

Adding Custom Shapes and Color Palettes

Adding annotations

Adding tooltips

Applying padding

Removing Gridlines, Row-Level and Column-Level Bands, and Shading

Summary

Exam Readiness Drill – Chapter Review Questions

8

Publishing and Managing Content

Introduction

Sharing Tableau Content

Publishing Workbooks

Publishing a Tableau Workbook

Publishing Data Sources

Publishing a Data Source

Exporting Content

Exporting to PDF

Cross-Tab Selected Data to Excel

Scheduling Data Updates

Extract Refreshes

Scheduling an Extract Refresh

Tableau Prep Flows

Managing Published Workbooks

Alerts

Creating a Data-Driven Alert

Subscriptions

Creating a Subscription

Summary

Exam Readiness Drill – Chapter Review Questions

9

Accessing the Online Practice Resources

Other Books You May Enjoy

Preface

The Tableau Certified Data Analyst Certification Guide is created to help you ace your Tableau Certified Data Analyst exam!

Data has been referred to as the new oil, and Tableau has consistently been at the top of the pack when it comes to data analytics software. For an analyst looking to excel in their job, or someone looking to move into the data industry, Tableau is the ideal tool. This book provides a detailed introduction to using Tableau and provides the necessary skills to pass the Tableau Certified Data Analyst exam. It will further set anyone up to use Tableau to enhance their career.

The Tableau Certified Data Analyst certification validates the fundamental knowledge required to explore, analyze, and present data and further your career in data analytics. This book is a best-in-class study guide that fully covers the Tableau Certified Data Analyst exam objectives and will help you pass the exam the very first time.

Complete with clear explanations, chapter review questions, realistic mock exams, and detailed solutions, this guide will help you master the core exam concepts and build the understanding you need to go into the exam with the skills and confidence to get the best result.

With the help of relevant examples, you will learn fundamental Tableau concepts such as transforming data and building dashboards. As you progress, you will delve into the important domains of the exam, including relationships, table calculations, and forecasting data.

This book contains a wide range of content and realistic scenarios that will give you everything you need to both pass the exam and utilize Tableau in your career.

The key features of the textbook include the following:

All topics relevant to the exam are covered in detailAdditional content is included to aid your understanding of TableauStep-by-step practical exercises within each topic are discussed to reinforce learningPractice questions and exam preparation tips are included to ensure you are confident with the types of questions that will come up during the exam

Whether you are studying independently or as part of a structured course, this textbook is designed to support your learning journey and help you achieve success in the Tableau Certified Data Analyst exam. We encourage you to engage actively with the material, practice regularly, and leverage the resources provided to maximize your understanding and proficiency in Tableau.

We wish you the best of luck in your Tableau certification journey and hope that this textbook serves as a valuable companion along the way.

Who This Book Is For

This book is for anyone interested in using Tableau to effectively explore and present data. You could be an IT professional looking to upskill or someone looking for a career in data.

There are no prerequisites for this book. This book will assist those with no prior knowledge of Tableau to prepare for the exam. Analysts with prior experience in exploring and presenting data will be able to utilize this book to improve and solidify their use of Tableau.

What This Book Covers

Chapter 1, Connecting to Data, introduces you to data source connections in Tableau. This includes the types of data sources that can be connected to and the configuration options when doing so.

Chapter 2, Transforming Data, takes you over the complete suite of tools and methods for transforming data with Tableau. Both Tableau Desktop and Tableau Prep data transformation methodologies are covered, as well as the data types available in Tableau. You will come out of the chapter with an understanding of how to clean and prepare data sources so that they are ready for analysis.

Chapter 3, Calculations, provides a detailed walk-through of the calculated field logic available in Tableau. Basic calculations are broken up by the data type they relate to. All available table calculations are described and fixed level of detail calculations are explained in terms of functionality.

Chapter 4, Grouping and Filtering, teaches you how to structure and filter data with Tableau. Tableau’s set, bin, group, and hierarchy functionalities are covered along with filtering methods and how to improve interactivity using parameters.

Chapter 5, Charts, covers how data can be visualized into charts, which is Tableau’s primary functionality. All relevant chart types are listed with explanations for the required setup along with additional chart-related functionality and analytical features.

Chapter 6, Dashboards, provides you with a detailed breakdown of how to combine multiple charts into a single piece of analysis primarily through dashboards but also using Tableau’s story feature. How to combine multiple charts in a dashboard is covered along with the types of objects that can be included on a dashboard and the available interactivity options.

Chapter 7, Formatting, walks you through how to apply formatting at a workbook level, including adding custom color palettes and shapes, formatting options available for individual charts, and how to customize the look of dashboards.

Chapter 8, Publishing and Managing Content, provides you with an introduction to publishing and managing content on Tableau Cloud. Once data has been presented in a visual format via charts, dashboards, or stories, the analysis needs to be shared with end users. This chapter covers how to share content as well as how to keep data fresh for end users.

Online Practice Resources

With this book, you will unlock unlimited access to our online exam-prep platform (Figure 0.1). This is your place to practice everything you learn in the book. How to access the resources. To learn how to access the online resources, refer to Chapter 9, Accessing the Online Practice Resources at the end of this book.

Figure 0.1: Online exam-prep platform on a desktop device

Sharpen your knowledge of Terraform concepts with multiple sets of mock exams, interactive flashcards, and exam tips accessible from all modern web browsers.

Download the Color Images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://packt.link/swloG .

Conventions Used

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and X (formerly Twitter) handles. Here is an example: “The COUNT function takes a single input of any data type and counts the number of items input (excluding null values). It is formatted as COUNT(value) and the example field with the values 1, null, and 3 would be formatted as COUNT([Field]) and would return 2.”

Bold: This indicates a definition or an important word or words that you see on screen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “Scroll down on the release page to the Download files section and click either the Windows or Mac download link to start the installation application download.”

A block of code is set as follows:

IF test1 THEN output1[ELSEIF test THEN outputn][ELSE defaultoutput]END

To Get the Most Out of This Book

In this book, Tableau-specific terms will be used to refer to areas of the Tableau Desktop interface. The following is a list of numbered terms that will be used throughout this textbook and can be identified in the following screenshot. A brief description of the functionality of each part of the interface is also provided:

Data pane: This is where the tables and fields from your data source can be found. These can be dragged onto the other areas of the interface to create charts.Canvas: This is where charts are displayed visually. Fields can be dropped directly onto the canvas positionally, and Tableau will usually incorporate the field into the chart accordingly.Columns and rows: Fields can be dragged onto columns and rows to create x and y axes or tables positioned as rows or as columns.Marks card: This is used to add detail to charts and visuals via color, text elements, tooltips, and a general level of detail for a visual. The specific mark type for the visual can be selected here as well (for example, pie chart, bar chart, or line chart).Filters shelf: Fields placed here can be configured to filter the chart to specific data points.Data Source tab: Selecting this tab will navigate to the data source interface where data sources can be configured.

Figure 0.2: Tableau Desktop Interface

Setting up Tableau

To complete the exercises in this textbook, you will need to download and install both Tableau Desktop and Tableau Prep Builder. If you do not have a license for Tableau, a two-week trial can be utilized. You will also need to register for a trial with Tableau Cloud.

This chapter will walk through the necessary steps for downloading and installing Tableau Desktop and Tableau Prep. It will also outline the process for signing up for a 14-day Tableau Desktop, Tableau Prep, and Tableau Cloud free trial.

Download and Install Tableau Desktop

Tableau Desktop is the Tableau tool that is used for analytics and data visualization. The bulk of the Tableau Certified Data Analyst exam consists of functionality within Tableau Desktop. There is a browser-based version of Tableau Desktop called Web Authoring, but there are some differences in functionality between the two tools, with Tableau Desktop having a wider range of features. It is recommended that you download and install Tableau Desktop and use it to complete the exercises contained within the textbook. If you already have Tableau Desktop installed can skip this section.

It is free to download and install Tableau Desktop, but a license is required to use it. If a license cannot be purchased, then a 14-day free trial can be started after installation.

To find the most recent version of the Tableau Desktop installer application, navigate to the following URL: https://www.tableau.com/support/releases. The page should look similar to the following screenshot (although the versions shown may be different).

Figure 0.3: The Tableau Desktop released versions page

Click on the large blue button at the center of the screen that says VIEW THE CURRENT VERSION. This will open up a sign-in page. If you already have a Tableau account, then log in here, otherwise, fill in the form and create an account. Once you have created an account and logged in, return to the downloads page and click the blue VIEW THE CURRENT VERSION button again.

The download page for the most up-to-date version of Tableau will now be open. The following screenshot was taken when version 2023.3 was the most current, but this will likely have changed.

Figure 0.4: Most recent Tableau version download page

Scroll down on the release page to the Download files section and click either the Windows or Mac download link to start the installation application download. The .exe file will begin to download and will likely be saved in the Downloads folder.

Figure 0.5: The Windows and Mac download links

Once the application installer has been downloaded, the installation process can begin. To install the application, the user must be signed in to the machine as an administrator. If the machine is Windows, then navigate to the downloaded .exe file and double-click to run it. To start the installation on a Mac, open the .dmg file and then select the .pkg installer.

The Tableau installer will now start and the installation steps can be walked through. Read through the terms and conditions and then tick to confirm they have been read. Decide whether to send product usage data to Tableau. The installation can be customized in terms of the location where Tableau Desktop will be installed, whether to include shortcuts, and whether to automatically check for Tableau product updates. When customization is complete, the Install button can be clicked followed by Yes to confirm and begin the installation.

Figure 0.6: The Tableau Desktop Windows installation wizard

Once the installation process is complete, Tableau will open automatically. The Tableau registration interface prevents the usage of Tableau Desktop. If a Tableau license has been purchased, then the Activate Tableau link can be clicked and the corresponding license key or Tableau Server or Cloud credentials can be put in. If opting for the 14-day free trial, the form can be filled in, and the Start trial nowbutton pressed.

Figure 0.7: Tableau Desktop product activation

Tableau Server and Tableau Cloud

Tableau Server and Tableau Cloud are web-based interfaces used to house and share Tableau content. Tableau Server is hosted by the end user, whereas Tableau Cloud is hosted by Tableau. Publishing and managing content on a Tableau Server or Tableau Cloud is a significant part of the Tableau Certified Data Analyst exam and will be covered in the final chapter of the textbook. Access to Tableau Server or Tableau Cloud will be required to complete the relevant publishing and managing content exercises. This section will walk through how to register for a free 14-day trial with Tableau Cloud. Those with access to a Tableau Server or Tableau Cloud that have at least a Creator license can skip the following section.

To start a free 14-day Tableau Cloud trial, log in to https://www.tableau.com/ and then navigate to https://www.tableau.com/en-gb/products/online/request-trial. The page will look similar to the following screenshot:

Figure 0.8: The Tableau Cloud free trial page

The blue button in the center that reads START YOUR FREE TRIAL can be clicked, which will scroll the page down to a registration form. Fill in the registration form and then click Get free trial. This will open a landing page where the blue START A FREE TRIAL button can be clicked.

Figure 0.9: Post registration form landing page

Finally, a site name can be typed in and a location for where the site should be hosted can be selected. Once the terms and conditions have been read and accepted, the ACTIVATE MY TRIAL button can be clicked to begin the free 14-day trial.

Figure 0.10: Tableau Cloud site name, location, and activation

It may take a few minutes, but the Tableau Cloud site will be created and then navigated to.

Tableau Desktop Practical Exercises

At the end of each section in each chapter, there will be practical exercises that will be a great way for you to reinforce the concepts learned throughout.

When it comes to Tableau Desktop, there is a default Tableau training data source that is readily available with each Tableau install. This is the data source that will be used for each exercise. The data source is called Sample – Superstore and can be selected from the bottom of the blue Connect pane on the left-hand side when Tableau Desktop is first opened.

Figure 0.11: The Sample – Superstore data source connection used for practical exercises

Information about the Exam

The Tableau Certified Data Analyst examination is a test of knowledge of and skills in the data visualization tool Tableau Desktop, the data cleaning and preparation tool Tableau Prep, and the content hosting product Tableau Server and Tableau Online.

There is no prerequisite for taking the Tableau Data Analyst exam and this textbook will walk through the content required to pass. Upon passing the exam, the title Tableau Certified Data Analyst is awarded with a digital badge confirmation on the certification website, Credly. The title lasts for two years, at which point the exam will have to be taken again to renew the title.

Direct experience with Tableau Prep and Tableau Desktop is considered essential for passing the Tableau Certified Data Analyst examination as it is geared toward aspiring data analysts looking to prove a base level of technical skill in these platforms. Theoretical knowledge of Tableau Cloud or Server is beneficial, as the examination covers them briefly in the text-based questions.

General advice from Tableau is for users to have six months of practical experience, but this is merely a benchmark, as the quality of experience can vary enormously. Users should therefore meet the following criteria:

Be comfortable navigating the user interfaces of Tableau Prep and Tableau Desktop

Understand the key features and functions covered in this guide, and be able to confidently apply them to an intermediate level of difficultyHave some experience creating basic charts and compiling these into simple interactive dashboards

Note that this study guide contains a host of practical questions that can form the baseline of a student’s practical experience.

The following section outlines the four domains covered in the Tableau Certified Data Analyst exam, followed by a description of the examination format and some useful tips for passing the exam.

Examination Domains

This section will describe the focus of each of the four examination domains, including what proportion of the examination they account for. The sections within each domain will be described along with the chapter the corresponding content can be found in within this textbook.

Connect to and Transform Data

The first examination domain is Connect to and Transform Data. This section accounts for 24% of the examination content, and is focused on the following:

Connecting to data from Tableau Desktop or PrepHow to clean, transform, and combine the data within those toolsCustomizing the final data source to be ready for analysis in Tableau Desktop

These topics are covered across four subsections:

Connect to Data SourcesPrepare Data for AnalysisPerform Data Transformation in Tableau PrepCustomize Fields

The first subsection, Connect to Data Sources, covers the different data source types that Tableau Desktop and Tableau Prep can connect to. This includes Tableau-specific files such as .hyper or .tde files, data sources that are published on Tableau Server/Online, spreadsheet files, and both direct connections to tables/views and custom SQL queries to relational databases. Knowledge of the advantages and disadvantages of the different data sources and when to choose one type over the other is also important. Similarly, an understanding of the benefits of live data source connections compared to data source extracts is required. Specific Tableau Desktop skills when it comes to how to replace data sources for existing content are also covered. This content is explored in Chapter 1, Connecting to Data.

The second subsection, Prepare Data for Analysis, covers basic data cleansing operations in Tableau Desktop. Knowledge of how to prepare data using Tableau’s Data Interpreter as well as how to pivot and split columns is required. General cleaning operations and organization of columns into folders are covered, as well as how to assess columns for key measures of data quality such as completeness, consistency, and accuracy.

You will need to know how to combine data sources within Tableau Desktop via relationships, joins, unions, and blending. It is important to understand how the data structure is impacted by these data combinations, as well as the benefits of one type over the other. Pre-filtering data using extract filters is another skill specific to Tableau Desktop that is required. Chapter 2, Transforming Data, covers the content in the subsection.

The third subsection, Perform Data Transformation in Tableau Prep, requires an understanding of how to clean, filter, transform, and combine data in Tableau Prep, including knowing which transformation is most suitable given a specific business scenario. How to perform unions, joins, aggregation, and pivoting is covered, and it is important to understand how each of these transformations will impact the granularity and structure of the data. Chapter 2, Transforming Data, also covers the content contained within this subsection.

The final subsection within the Connect and Transform Data domain is Customize Fields. This subsection is specific to Tableau Desktop and covers the final customization of columns in preparation for data visualization. Required knowledge includes how to rename columns, default property customization, such as changing the field type and sort order, and aliasing names. It is important to fully understand the distinction between discrete and continuous fields, as well as dimensions and measures, particularly the implications of the combination of these field types. The content for this subsection is covered in Chapter 1, Connecting to Data.

Explore and Analyze Data

Explore and Analyze Data is the largest examination domain, accounting for 41% of the examination’s content. The domain covers the bulk of Tableau Desktop’s features for exploring and analyzing data, including custom logic using calculated fields, the creation of dynamic view-based table calculations, the various methodologies for filtering data, and how to use Tableau’s parameters to increase interactivity. The options available for structuring data is required knowledge and so is how to create charts using geographic field types. Finally, Tableau’s analytics features are all included – from reference lines to predictive models.

The Create Calculated Fields subsection requires you to know how to create custom logic in Tableau Desktop using Tableau’s own calculated field language. Simple logic (such as converting data types) is required as well as knowledge of how to aggregate measures and write string and number functions. Basic logical expressions (such as if and case statements) must be understood, as well as the various date functions available. The most complex type of calculation needed for the examination is the Level of detail calculations that allow Tableau users to fix data at a specific level of aggregation. The required calculations will be covered in Chapter 3, Calculations.

The second subsection covers the creation of quick table calculations. Quick table calculations are logical calculations that work on aggregated data in the view and are created via the interface selections. The examination can include questions on creating quick table calculations to show a moving average, a percent of the total, a running total, a difference or percent of a difference, a percentile, and a compound growth rate. It is important to understand what these table calculations show in the view and how to customize them to work in different directions or based on different levels of aggregation. Quick table calculations will be covered in Chapter 3, Calculations.

The Create Custom Table Calculations subsection builds on the quick table calculations by requiring an understanding of how to use table calculations to implement either date-based or ranking logic. Date-based logic includes how to use table calculations to dynamically display year-to-date, month-to-date, and year-over-year values. Ranking logic includes adding IDs or rank values to the view using either index, ranking, first, or last table calculations. Custom table calculations will be covered in Chapter 3, Calculations.

How to create and use filters is a subsection focusing on limiting the data shown in the view using Tableau Desktop’s various filtering methods. The difference between filtering dimensions and measures must be understood and it is also important to understand the types of filtering available for dimensions, such as top and bottom N, include, exclude, wildcard, and conditional. The order in which different types of filters occur is covered, including the impact of adding filters to context. You will also need to know how to apply a filter across multiple sheets and data sources. This content will all be covered in Chapter 4, Grouping and Filtering.

Parameters are user-created static variables that are available in Tableau Desktop. Knowledge of how to apply parameters in calculations, filters, and reference lines is needed for the examination and this will be covered in Chapter 4, Grouping and Filtering.

The next subsection within Explore and Analyze Data focuses on how to structure the data. This section includes the various methodologies Tableau Desktop users can implement to create groupings within their data. Fields can be grouped into hierarchies where some field values represent a higher or lower-level grouping of the values of other fields. Field values can also be manually grouped together, in the case of dimensions, using Tableau’s groups or sets. Dynamic grouping can also be set up for dimensions using sets and can be set up for measures using bins. The functionality available for all the mentioned methods of data structuring must be understood, and these will be covered in Chapter 4, Grouping and Filtering.

Geographic data can be mapped in Tableau via symbol, heat, density, and choropleth (filled) maps. The difference between these as well as an understanding of how to create each is required for the examination. Geographic chart creation will be covered in Chapter 5, Charts.

The final subsection in the Explore and Analyze Data domain involves summarizing, modeling and customizing data by using the analytics feature. You are required to know how to use the analytics feature to add subtotals and totals, reference lines and bands, average lines, trend lines, and distribution bands. Knowledge of advanced analytics features such as default and customized forecasting and the creation of predictive models is also required. Chapter 5, Charts, ends with an explanation of each Analytics feature.

Create Content

The third examination domain is again specific to Tableau Desktop only and covers 26% of the examination content. It focuses on the creation of content, namely how to create the basic chart types available in Tableau and then how to combine them into dashboards and stories. Dashboard development in terms of the interactivity options available as well as formatting capabilities are also covered.

The Create Charts subsection is comprehensive, requiring users to know how to create bar charts, line charts, pie charts, highlight tables, scatter plots, histograms, tree maps, bubbles, data tables, Gantt charts, box plots, area charts, dual axis charts, and combo charts. You need to know how to create these charts from scratch as opposed to using Tableau’s Show Me functionality. This means you will need to understand the key areas of the Tableau Desktop interface, including the rows and columns shelves as well as the marks card, and how placing different field types on each of these sections will result in different types of charts being created. Sorting of the data within the charts must also be understood, including custom sorting. Chart creation and sorting is covered in Chapter 5, Charts.

The creation of dashboards to combine worksheets (charts) into a consolidated piece of analysis is also covered. This means you will need to know how the various layout options available in Tableau Desktop work, and more specifically how layout containers work. You also need to know what the different dashboard objects are and how to bring them onto a dashboard. The combination of dashboards into stories must also be understood. Dashboard and story creation are covered in Chapter 6, Dashboards.

Knowledge of the interactivity options available when creating dashboards is another requirement for the examination. This includes how to apply filters to a view, and how to add interactivity to charts in the form of hover, click, and menu options. You will need to know what types of actions are available, including filtering, highlighting, and URL actions, as well as how to configure them and provide guiding sentences if required. You need to know how to implement navigation via buttons as well as how to implement sheet swapping using parameters or sheet selectors. The functionality for this subsection is covered in Chapter 6, Dashboards.

The final subsection of the domain is Format Dashboards. This section requires you to be able to use all the formatting options available to make charts look more presentable and focus the analysis on key insights. This includes how to customize color, fonts, shapes, and styling using the marks card as well as how to add custom tooltips. Cleaning up charts by removing gridlines and table formatting must also be understood. You must also know how to add annotations to charts to point out key insights. At the dashboard level, you will need to know how to add padding to dashboards to create whitespace and avoid a cluttered look, and you must also know how to customize device-specific layouts for dashboards. Tableau has standard shapes and color schemes available to all users but an understanding of how to add custom shapes and color schemes to Tableau Desktop is also required. The content for this subsection is covered in Chapter 7, Formatting.

Publish and Manage Content on Tableau Server and Tableau Cloud

The final examination domain, Publish and Manage Content on Tableau Server and Tableau Cloud, is mainly focused on the sharing and managing of content in Tableau Server/Online but also requires knowledge of uploading content from both Tableau Desktop and Tableau Prep. This is the smallest domain, accounting for 9% of examination content. The domain covers publishing content from Tableau Desktop and Tableau Prep, scheduling data refreshes and Tableau Prep flows on Tableau Server/Online, and managing alerts and subscriptions on and to published workbooks.

The first subsection, Publish Content, requires an understanding of how to publish workbooks and data sources to Tableau Server/Online from Tableau Desktop and Tableau Prep. How to print and export from Tableau Desktop and Tableau Server/Online must also be understood, along with the print and export format types available. This content is covered in Chapter 8, Publishing and Managing Content.

Scheduling data updates must also be understood in terms of how to schedule both an extract refresh and a Tableau Prep Workflow on Tableau Server/Online. Tableau Server and Online scheduling will be covered in Chapter 8, Publishing and Managing Content.

Tableau user alerts on data points within workbooks and subscriptions to workbooks must be understood in terms of how to set up, configure, and manage them. This will also be covered in Chapter 8, Publishing and Managing Content.

Examination Format

The following applies to both the test center and remote/online examination format unless otherwise stated.

Prerequisites

This examination does not require any pre-existing qualifications. A Tableau account is required to book and take the examination. If you do not already have a Tableau account, you can do so by following official Tableau instructions at https://mkt.tableau.com/files/CertificationAccountCreation.pdf. As part of this process, the Tableau/Salesforce Terms of Service must also be agreed to.

Once created, your Tableau account should be used to log in to the Pearson VUE Certification portal using the following link: https://cp.certmetrics.com/tableau/en/home/. Once preliminary information has been entered, and terms agreed upon, the user can schedule directly with Pearson VUE, who proctor the examination on behalf of Tableau. A legal, photographic form of identification must be shown to the proctor on examination day before the examination begins to confirm your identity. Further information on ID requirements may be found under View ID requirements here: https://home.pearsonvue.com/tableau/onvue. It is important to ensure the first and last names used for your Tableau account are identical to the name on your chosen form of identification, or examination access may be denied without recompense.

The online examination is accessible only when a number of minimum technical requirements are met. Crucial amongst these are a computer with video capabilities, an internet connection of consistently high quality, and a screen resolution of at least 1,024 x 768. A comprehensive list is available at https://home.pearsonvue.com/op/OnVUE-technical-requirements.

These standards and checks are pre-established when the examination is taken at a Pearson VUE testing center.

When beginning the examination, participants must also agree to the terms and conditions of testing, which includes a strict non-disclosure agreement.

Examination Length

The examination is 2 hours long in total, 93 minutes of which are allocated to the examination itself. Approximately 8 minutes are permitted for the administrative tasks of signing the non-disclosure agreement and completing the tutorial; the tutorial describes the question types the user can expect and familiarizes the participant with the user interface.

The examination environment will open 30 minutes prior to the scheduled examination time. Participants are advised to join as soon as possible after this time to conduct environment, system, and ID checks, which occur live with a proctor.

Cost

There is a USD 250 base fee, excluding any taxes, such as VAT – this can vary based on location.

Note

Should the examination need rescheduling, a fee of USD 25 (plus required taxes) applies.

Assessment Limitations

The Tableau Certified Data Analyst examination is a “closed book” exam. No resources of any nature, be it digital or hard copy, are permitted to be present or used during the examination.

Language and Accessibility

The examination is most commonly conducted online, but it may also be taken at one of Pearson VUE’s examination centers. There is no material difference between taking the examination online or at a test center, but if your machine is at risk of failing system checks, it is recommended to take the examination at a center. The system checks can be run from the following page: https://system-test.onvue.com/system_test?customer=pearson_vue&clientcode=CHECKPOINT&locale=en_US. The examination is currently available in English and Japanese only.

Should participants have specific accessibility requirements, adjustments may be requested by completing the following form: https://app.smartsheet.com/b/form/2d4c22dfbbd74aee9aea5d07c223f676. Please note that terms are to be agreed upon prior to scheduling an exam, and students may be required to submit appropriate evidence as part of their appeal.

Question Structure

The Tableau Certified Data Analyst certification contains 55 questions, split across three sections. Questions from any of the four domains discussed previously may appear in these sections, in any order. The majority of these test theoretical knowledge; expect approximately 45 static, text-based questions. The format of these may be any of the following:

Multi-select: Four potential answers are presented, in which one or more may be correctMulti-choice: Four potential answers are presented, with a single correct answerActive screen: An image is presented with interactive regions that the user must select in response to the question

There are also approximately 10 practical questions, which are administered in Tableau itself. (Tableau is launched in a controlled manner directly inside the examination environment; this set-up process occurs automatically and requires no expertise on behalf of the examination participant.)

The examination is split into three sections: the first set is static (theoretical); the second practical, completed within an instance of Tableau Desktop; and the third is once again static. The static questions can be marked for review, which makes them easy to return to at the end of the section. All prior questions can be revisited and updated until the participant moves to the next section, at which time sections are closed and answers locked. The domains covered here are spread roughly evenly across each of the three sections.

Pass Criteria and Results

A passing grade of 750 is required. (Note that this score is not the true score achieved, but a mathematically calculated one to standardize difficulties across examinations).

Tableau policy is to send examination results to the email address associated with the participant’s account within 48 hours of the examination finishing. (Note that there may be a short delay before the certification is registered on the participant’s account and/or issued at Credly.)

Share Your Thoughts

Once you’ve read Tableau Certified Data Analyst Certification Guide, we’d love to hear your thoughts! Please click here to go straight to the Amazon review page for this book and share your feedback.

Your review is important to us and the tech community and will help us make sure we’re delivering excellent quality content.

Download a Free PDF Copy of This Book

Thanks for purchasing this book!

Do you like to read on the go but are unable to carry your print books everywhere?

Is your eBook purchase not compatible with the device of your choice?

Don’t worry, now with every Packt book you get a DRM-free PDF version of that book at no cost.

Read anywhere, any place, on any device. Search, copy, and paste code from your favorite technical books directly into your application.

The perks don’t stop there, you can get exclusive access to discounts, newsletters, and great free content in your inbox daily.

Follow these simple steps to get the benefits:

Scan the QR code or visit the link below:

https://packt.link/free-ebook/9781803243467

Submit your proof of purchase.That’s it! We’ll send your free PDF and other benefits to your email directly.

1

Connecting to Data

Introduction to Data

You are likely to have a basic grasp of the concept of data – it is difficult to avoid in a world increasingly driven by information, in which this information is both easier to gather and more valuable than ever. However, it is useful to begin with a basic definition.

Take, for example, a coffee chain store. Every day for the past five years, there has been an abundance of data collected for the number of sales, the number of cups of coffee sold, the different types of coffee sold, and even the stocks of coffee. A regional store manager may want to be able to see how well their sales are doing, which stores are performing best, and whether their specialty drinks are selling better than the classics. Five years of data can be hard to analyze in spreadsheets, and this is where Tableau can be the ideal tool for use. Tableau can connect to the data source and build dynamic dashboards that can help answer these questions. It can even define any outliers that exist, allowing the coffee chain to make data-driven decisions to help improve its business.

The following topics will be discussed in this chapter:

Connecting to sourcesData structureChoosing an appropriate data source typeConnecting to Tableau Server or Tableau CloudConnection management

This chapter is designed to inform you how to connect to data in Tableau with different data sources and servers that are available.

Making the Most Out of This Book – Your Certification and Beyond

This book and its accompanying online resources are designed to be a complete preparation tool for your Tableau Certified Data Analyst Certification Guide.

The book is written in a way that you can apply everything you’ve learned here even after your certification. The online practice resources that come with this book (Figure 1.1) are designed to improve your test-taking skills. They are loaded with timed mock exams, interactive flashcards, and exam tips to help you work on your exam readiness from now till your test day.

Before You Proceed

To learn how to access these resources, head over to Chapter 9, Accessing the Online Practice Resources, at the end of the book.

Figure 1.1: Dashboard interface of the online practice resources

Here are some tips on how to make the most out of this book so that you can clear your certification and retain your knowledge beyond your exam:

Read each section thoroughly.Make ample notes: You can use your favorite online note-taking tool or use a physical notebook. The free online resources also give you access to an online version of this book. Click the BACK TO THE BOOK link from the Dashboard to access the book in Packt Reader. You can highlight specific sections of the book there.Chapter Review Questions: At the end of this chapter, you’ll find a link to review questions for this chapter. These are designed to test your knowledge of the chapter. Aim to score at least 75% before moving on to the next chapter. You’ll find detailed instructions on how to make the most of these questions at the end of this chapter in the Exam Readiness Drill - Chapter Review Questions section. That way, you’re improving your exam-taking skills after each chapter, rather than at the end.Flashcards: After you’ve gone through the book and scored 75% more in each of the chapter review questions, start reviewing the online flashcards. They will help you memorize key concepts.Mock Exams: Solve the mock exams that come with the book till your exam day. If you get some answers wrong, go back to the book and revisit the concepts you’re weak in.Exam Tips: Review these from time to time to improve your exam readiness even further.

This chapter covers the following main topics:

The benefits of cloud computingCloud deployment modelsCloud service modelsThe core concepts of Azure

Connecting to Sources

The first step in virtually any data analytics process is to connect to data. Tableau (and machines in general) cannot natively know where, how, or when to look for data. This link must be initially set up by the user.

Tableau offers many options for data connectivity, from simple spreadsheets on a local device to large online repositories accessible anywhere in the world. Naturally, with such varied means of storing data, the process for setting up these connections differs. Nonetheless, the location must always be specified in some way.

Data often contains sensitive information and is relied upon to represent real events. It is, therefore, important to maintain its integrity. Some kind of authentication is often required to prove user identity, especially for data stored on the cloud and intended to be accessed remotely; this most commonly involves entering credentials (such as a username or password).

It is important to note that none of the services in the Tableau Suite (such as Desktop, Prep, or Server) have the tools or permissions to change the underlying source data. Tableau can only edit duplications of the data contained within its own environment.

Organizations with a base level of data maturity, typically medium to large companies, often have established data sources and servers, such as Teradata, Snowflake, or even Tableau Server, which Tableau users are expected to utilize. However, it is certainly possible for data analysts and those in similar roles to find themselves establishing new sources. In any scenario, there are requirements and best practices for data that all users should be aware of.

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.

Choosing an Appropriate Data Source Type

Before any user or developer can start building a visualization, an appropriate data source must be defined. Without data, there will be no visuals to be built and no stories to be told. Multiple factors should inform decision-making when it comes to choosing a data source. In summary, these include the following.

Content and Quality

The following points are key for any data preparation for a developer to be able to analyze data properly. It is important for you to familiarize yourselves with these practices as you will be questioned about them in the exam.

Level of detail: Dimensions and Measures

Tableau should be approached not merely as a tool for data visualization. Charts should be created and used thoughtfully as a means of answering business questions. Therefore, data should be selected with a goal in mind: does it contain the fields (columns) and records (rows) required to answer the questions at hand?

When it comes to fields, data should contain the appropriate dimensions (to divide the view) and measures (for assessable metrics). It is impossible to review the relative performance of each salesperson, for example, without their name or other unique identifiers alongside a Profit field. And if those fields are incomplete – lacking all salespeople, or profits for certain months of the year – then accurate conclusions cannot be drawn.

Data Quality

The previous point touched on completeness as an important facet. This can be expanded further: any data source used should have an appropriate level of completeness, accuracy, and consistency for the resulting insights to be valuable. You need to make sure that the data used is complete, all field names are named appropriately, and the spellings are kept consistent. Please see Chapter 2, Transforming Data, for further details.

Technical Requirements

This section will look into the technical requirements that need to be considered when building a report. The purpose is to inform you about the different data connections that can be made and their performance.

Performance: Data Size and Structure

Tableau is capable of processing large volumes of data, but performance sits on a curve: the larger the dataset, the more computational power is required to access and process it. There is no fixed rule for when performance will meaningfully decrease, as this depends on a complex combination of factors, including the specification of the machine running the query (one with lots of resources, such as RAM, can handle greater quantities of data). It is fair to say that a data source with dozens of columns will be processed slower than one with a handful of them; similarly, a source with millions or even billions of records will be less performant than one with a few hundred.

There are stricter limitations for data sources hosted on Tableau Server or Tableau Cloud rather than a local machine; for example, joins and relationships cannot be established, only blends. These are covered in more detail in Chapter 8, Publishing and Managing Content.

It is worth noting that Tableau generally prefers data that is long rather than wide in structure: that is, Tableau can handle more records better than it can handle more fields.

Data Format and Compatibility with Tableau

Users should be sure that a connector exists natively for the given data source type. This can be a type of file that exists locally on the computer such as an Excel file.

Users should consider whether data is accessed live or saved as an extract – that is, whether the data is a saved snapshot, such as an extract, or whether it would run on a real-time basis, such as a live data source.

The description and limitations of these connections will be explained further in this chapter.

Microsoft Excel (.xlsx) and Comma-Separated Values (.csv) Types

This section is written to differentiate between Excel and CSV files and discuss how they are connected to Tableau. Because of their simplicity and familiarity with users, these are the most likely files used to connect to Tableau.

Excel is a specialist spreadsheet format from Microsoft that has been popular for data storage for decades.The comma-separated values (CSV) file is named as such because values within it are distinguished (delimited) by commas. Each line in the file constitutes a distinct record. The CSV format is generic and not associated with a particular software or service, though files are often opened and used with Microsoft Excel or Google Sheets.

The plain-text format of CSVs is simple to create and straightforward for programs to read, making it easier to move data between systems or locations without complicated parsing steps. CSV files appear no different from spreadsheets when opened in Excel or Tableau – almost all software designed for use with data automatically displays the mass of comma-delimited text in a tabular structure of columns and rows.

As both file types are commonplace, there is a low barrier to entry – the formats are familiar to a wide range of computer users. However, as with most files, these types offer a snapshot of data in time; they are not automatically updated in the way that connections to live source systems are.

Note that CSV files typically cast values as plain text, even when all values are in a specific format – fields that are fully numerical, for example, may still be returned as strings. When first opened in Tableau Desktop, fields often need converting to appropriate data types such as String, Integer, or Float, so that there will be no errors when building calculations. Excel files have a hard limit of approximately one million records, determined by the maximum memory available in the Microsoft Excel software itself; note that this also applies to imported CSVs.

Relational Databases

While using Excel and CSV is a simple and easy way to connect to data in Tableau, these files can easily be changed by human error and are not dynamic. Most organizations have outgrown using Excel and CSV for the following reasons:

They require data that can be found quickly when needed and is trusted to be reliable and accurateThe solutions need to be able to comfortably handle the natural growth of data and the number of people wanting to access and manipulate itThe files can often be duplicated and shared freely, risking unwarranted accessAlternative solutions offer greater opportunities to connect from other locations, rather than a single local machine

Relational databases are often a reliable means of achieving these benefits. They are data storage systems that organize information in the familiar tabular structure, with rows and columns; when databases