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How to Become a Data Analyst
My Low-Cost, No Code Roadmap for Breaking Into Tech
Taschenbuch von Annie Nelson
Sprache: Englisch

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Beschreibung

Discover how to start a new career in data analytics from someone who s been in your shoes

In How to Become a Data Analyst: My Low-Cost, No Code Roadmap for Breaking into Tech, self-taught data analyst and Tableau consultant Annie Nelson delivers an exciting and insightful roadmap to transitioning from an unrelated career to a promising new one in data analytics.

You'll discover the key skills in the industry, how to learn them, and how to prove your knowledge to potential employers. Along the way, you'll learn how to avoid some common missteps and mistakes, including certificate- and course-hopping.

How to Become a Data Analyst skillfully shows you how to get your portfolio going and outlines a framework for your initial projects. Engaging and informative, this reliable resource takes you on a learning journey that will allow you to make meaningful and impressive contributions in your new role. It also shows you how and where to look for jobs and how to navigate a typical data interview.

An indispensable resource for anyone interested in pursuing a new career in data analytics, How to Become a Data Analyst is the step-by-step guide you've been waiting for.

Discover how to start a new career in data analytics from someone who s been in your shoes

In How to Become a Data Analyst: My Low-Cost, No Code Roadmap for Breaking into Tech, self-taught data analyst and Tableau consultant Annie Nelson delivers an exciting and insightful roadmap to transitioning from an unrelated career to a promising new one in data analytics.

You'll discover the key skills in the industry, how to learn them, and how to prove your knowledge to potential employers. Along the way, you'll learn how to avoid some common missteps and mistakes, including certificate- and course-hopping.

How to Become a Data Analyst skillfully shows you how to get your portfolio going and outlines a framework for your initial projects. Engaging and informative, this reliable resource takes you on a learning journey that will allow you to make meaningful and impressive contributions in your new role. It also shows you how and where to look for jobs and how to navigate a typical data interview.

An indispensable resource for anyone interested in pursuing a new career in data analytics, How to Become a Data Analyst is the step-by-step guide you've been waiting for.

Über den Autor

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.

Inhaltsverzeichnis

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

Details
Erscheinungsjahr: 2024
Fachbereich: Betriebswirtschaft
Genre: Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Taschenbuch
Inhalt: Preface xiiiIntroduction xixPart I The Fun PartChapter 1 Is Data Analytics Right for Me? 3What Does a Data Analyst Do Every Day? 4Hours/Time 6In-Person Data Jobs 9What Makes a Good Analyst? 10Planning 12Organization 13Critical Thinking/Strategy 14Collabo
ISBN-13: 9781394202232
ISBN-10: 1394202237
Sprache: Englisch
Herstellernummer: 1W394202230
Einband: Kartoniert / Broschiert
Autor: Nelson, Annie
Hersteller: Wiley
Maße: 225 x 151 x 15 mm
Von/Mit: Annie Nelson
Erscheinungsdatum: 04.01.2024
Gewicht: 0,328 kg
Artikel-ID: 127160531
Über den Autor

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.

Inhaltsverzeichnis

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

Details
Erscheinungsjahr: 2024
Fachbereich: Betriebswirtschaft
Genre: Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Taschenbuch
Inhalt: Preface xiiiIntroduction xixPart I The Fun PartChapter 1 Is Data Analytics Right for Me? 3What Does a Data Analyst Do Every Day? 4Hours/Time 6In-Person Data Jobs 9What Makes a Good Analyst? 10Planning 12Organization 13Critical Thinking/Strategy 14Collabo
ISBN-13: 9781394202232
ISBN-10: 1394202237
Sprache: Englisch
Herstellernummer: 1W394202230
Einband: Kartoniert / Broschiert
Autor: Nelson, Annie
Hersteller: Wiley
Maße: 225 x 151 x 15 mm
Von/Mit: Annie Nelson
Erscheinungsdatum: 04.01.2024
Gewicht: 0,328 kg
Artikel-ID: 127160531
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