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

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

          
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About the Book

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.

Table 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 Sales Project 111 Dirty Data + Case Study 112 Dirty Data + Case Study + Hints 113 Clean Data + Case Study 114 Semi-Structured Case Study with Hints 115 Busy Times 116 Pizzas During Peak Periods 116 Best- and Worst-Selling Pizzas 116 Average Order Value 117 Seating Capacity 117 Final Thoughts 118 SQL Project Creation Advice 119 From the Portfolio to the Job Search 121 Getting in the Mindset for Projects 122 Part III The Hard Part 125 Chapter 8 Starting Your Job Search 127 How Do I Know When I Am Ready to Start My Job Search? 127 Where and How Should I Look for Jobs? 129 Searching Posts 129 Job Titles 130 Where Can I Find Salary Information? 131 What Is the Data Analyst Career Progression? 131 Chapter 9 Résumé Building and Setting Your Public Image 137 How Do I Write a Résumé? 138 Length 138 Technical Skills 141 Relevant History 142 Formatting 142 Use Metrics 143 How Do I Optimize My LinkedIn? 144 History 144 Connections 146 Headline 149 Profile Photo 150 Can You Tell Me How to Network? 151 What Is Networking (and What Is It Not)? 151 Networking and Messaging on LinkedIn 153 Messaging Jobs Directly 154 Networking Events 156 Interviewing 157 Bonus Tip: An Idea for Your First LinkedIn Post 158 Chapter 10 Stages of Data Interviews 161 Why Do Interviews Take So Long? 161 Can You Tell Me More about the Interview Stages? 162 Phone Screen 163 Meeting the Hiring Manager 165 Behavioral Interview 166 Technical Interview 166 Panel Interview 169 Culture Fit 170 Follow-up 171 How I Handled Some Common How-Tos 172 Tell Me about Yourself 173 How to Come Up with Good Questions 175 Resources 180 Teal 180 Maven Analytics 181 Content Creators/Small Businesses 182 Working with Data Creators 183 Using AI 184 Chapter 11 How to Use ChatGPT to Aid Your Job Search 185 Writing a Résumé 185 Writing Cover Letters 186 Practicing for Interviews 186 Phone Screen 186 Technical Interview 189 Behavioral Interview 189 Writing Follow-Up Emails 191 Be Specific 192 Chapter 12 My Job Search 195 “Open to Work?” 195 Beginning to Search 197 Getting Reponses (and Rejections) 200 Pivoting 202 Interviewing 204 Decision Day 207 Part IV The Bonus Part 209 Chapter 13 After the Job Offer 211 Starting the Job 212 Dealing with Imposter Syndrome 213 Steps to Success 214 What It’s Like Working Remotely 215 Some Things About Tech That Surprised Me 217 121s 217 Home Office Stipend 217 Company Party/Offsites 218 Meetings 218 Referrals 219 Layoffs 220 Problem‐ Solving 221 Travel 222 Data Has Changed My Life 224 Chapter 14 Preparing for/Recovering from a Layoff 225 Don’t Ignore Red Flags 225 Resumes and Networking—Restarting the Job Search 226 Updating my Portfolio 229 The Layoff 230 Adjusting for Your Situation 235 Closing Thoughts 236 Appendix A Data Analytics Roadmap Checklist 239 Appendix B Tableau Tips 241 Appendix C My Data Analyst Journey 249 Acknowledgments 257 About the Author 259 Index 261


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Product Details
  • ISBN-13: 9781394202232
  • Publisher: John Wiley & Sons Inc
  • Publisher Imprint: John Wiley & Sons Inc
  • Height: 229 mm
  • No of Pages: 288
  • Spine Width: 13 mm
  • Weight: 295 gr
  • ISBN-10: 1394202237
  • Publisher Date: 25 Dec 2023
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Sub Title: My Low-Cost, No Code Roadmap for Breaking into Tech
  • Width: 152 mm


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