How to Become a Data Analyst - My Low-Cost, No Code Roadmap for Breaking Into Tech

Start a brand-new career in data analytics with no-nonsense advice from a self-taught data analytics consultant
 
In How to Become a Data Analyst: My Low-Cost, No Code Roadmap for Breaking into Tech, data analyst and analytics consultant Annie Nelson walks you through how she took the reins and made a dramatic career change to unlock new levels of career fulfilment and enjoyment. In the book, she talks about the adaptability, curiosity, and persistence you'll need to break free from the 9-5 grind and how data analytics--with its wide variety of skills, roles, and options--is the perfect field for people looking to refresh their careers.
 
Annie offers practical and approachable data portfolio-building advice to help you create one that's manageable for an entry-level professional but will still catch the eye of employers and clients. You'll also find:
* Deep dives into the learning journey required to step into a data analytics role
* Ways to avoid getting lost in the maze of online courses and certifications you can find online--while still obtaining the skills you need to be competitive
* Explorations of the highs and lows of Annie's career-change journey and job search--including what was hard, what was easy, what worked well, and what didn't
* Strategies for using ChatGPT to help you in your job search
 
A must-read roadmap to a brand-new and exciting career in data analytics, How to Become a Data Analyst is the hands-on tutorial that shows you exactly how to succeed.

List of contents

Preface xiii
 
Introduction xix
 
Part I The Fun Part
 
Chapter 1 Is Data Analytics Right for Me? 3
 
What Does a Data Analyst Do Every Day? 4
 
Hours/Time 6
 
In-Person Data Jobs 9
 
What Makes a Good Analyst? 10
 
Planning 12
 
Organization 13
 
Critical Thinking/Strategy 14
 
Collaboration/Communication 15
 
What Tools Should I Learn? 17
 
Excel/Google Sheets 17
 
SQL 19
 
Tableau/Power BI 21
 
Python 24
 
R 25
 
Which Entry-Level Tech Job Is Right for Me? 25
 
What's Next 29
 
Chapter 2 Understanding the Paths into Data 31
 
How Hard Is It to Become a Data Analyst? 32
 
What Are My Options for Getting into Data Analytics? 34
 
Transitioning from an Analyst-Adjacent Role 35
 
Getting a Degree 35
 
Boot Camps 36
 
When a Boot Camp May Be the Right Option for You 37
 
How to Pick a Good Boot Camp 38
 
DIY Approach 40
 
How I Decided on the DIY Approach 41
 
Chapter 3 Designing Your Data Analyst Roadmap 45
 
Can You Shows Me Your Data Analyst Roadmap? 46
 
Building Your Roadmap 46
 
Step 1: Skill Development 47
 
Step 2: Building a Portfolio 49
 
Step 3: Getting Yourself Ready to Job Search 52
 
How Do I Choose the Best Course? 53
 
What Makes a Good Course 55
 
Learning Styles 55
 
Budget 56
 
Support 57
 
Interests 58
 
Time Constraints 59
 
Getting Started for Free 60
 
When Not to Pick a Course: How to Avoid Course Hopping 61
 
Chapter 4 My Experience with Data Analytics Courses 63
 
The Beginning 63
 
The Google Certificates Course 64
 
Learning SQL 65
 
Learning Tableau and R 68
 
Finishing the Course 70
 
What Came Next 72
 
Changing Careers 72
 
Course Hopping: When Is Taking Another Course Worth It? 73
 
Part II The Scary Part 77
 
Chapter 5 Introduction to Portfolios 79
 
What Is a Data Analytics Portfolio? 79
 
Can I See an Example? 80
 
Why Do I Need a Portfolio? 81
 
As an Analyst 81
 
As a Job Seeker 82
 
If I Have Experience from Another Job, Do I Still Need a Portfolio? 83
 
Chapter 6 Portfolio Project FAQ 85
 
How Do I Find Free Data? 86
 
Maven Analytics 87
 
Real World Fake Data 89
 
Your Data 89
 
Data from Me! 90
 
SQL Practice 91
 
Other Places 92
 
Can You Tell Me More about Completing Projects? 93
 
How Do I Get Started on Projects? 93
 
Does My Project Need to Be Original and Industry Specific? 95
 
How Do I Know When a Project Is Ready? 96
 
Where Do I Publish and Store My Work? 96
 
How Many Projects Do I Need? 98
 
Should I Share My Work Publicly? 99
 
Project Time! 100
 
Chapter 7 Portfolio Project Handbook 101
 
Project Levels: What Separates a Beginner from an Intermediate Project? 102
 
First Project 102
 
Beginner Project 103
 
Intermediate Project 103
 
Regular Tableau User 104
 
Guided Projects 104
 
New Year's Eve Resolutions Project 104
 
Case Study: New Year's Eve Resolutions Project 105
 
Semi-Structured Case Study with Hints 106
 
Final Thoughts 108
 
Help Desk Project 108
 
Case Study: Help Desk Project 109
 
Semi-Structured Prompts 109
 
Pizza Sales Project 111
 
Case Study: Pizza S

About the author

ANNIE NELSON is a self-taught data analyst and Tableau consultant, as well as a popular commentator on TikTok (@anniesanalytics) where she shares her experiences and journey through the world of data analytics. She works remotely, balancing her self-scheduled work with frequent trips abroad and growing her substantial following on social media.

Product details

• Authors: Annie Nelson
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Paperback / Softback
• Released: 27.02.2024
• EAN: 9781394202232
• ISBN: 978-1-394-20223-2
• No. of pages: 288
• Subjects: Non-fiction book > Politics, society, business > Business administration, companies; Social sciences, law, business > Business > Business administration; Datenanalyse, Personalwesen, Business & management, algorithms and data structures, Wirtschaft u. Management, Personal Career Development