Becoming a Data Analyst: A beginner’s guide to kickstarting your data analysis journey

Get started with your data science career with in-depth explanations of key concepts, real-world applications, and career advice

Key Features

• Conquer all essential data analysis techniques using real-world examples, case studies, and hands-on exercises
• Get to grips with ethical considerations in data analysis while developing problem-solving and critical thinking skills
• Get career guidance and tips for building a portfolio, regardless of your background or experience

Book Description

Are  you interested in becoming a data analyst, but don't know how to begin?  Look no further than this comprehensive book that covers everything you  need to know to get started with data analysis.

Becoming  a Data Analyst will teach you about data collection techniques, data  cleaning and pre-processing, exploratory data analysis, statistical  analysis, data wrangling and transformation, data modeling, data  presentation and communication, and ethical considerations in data  analysis.

Each chapter provides clear, step-by-step  guidance on how to conduct data analysis using various techniques and  tools. You'll also benefit from real-world examples, case studies,  hands-on exercises, and visual aids such as diagrams, charts, and graphs  to help you understand complex concepts and data.

In  addition to practical skills, this book emphasizes problem-solving  skills, showing you how to identify and solve real-world problems using  data analysis techniques. It also addresses ethical considerations in  data analysis, such as data privacy and bias, and provides guidance on  how to conduct data analysis in an ethical and responsible manner.

Whether  you're just starting out or looking to take your data analysis skills  to the next level, Becoming a Data Analyst is the essential guide you  need to succeed.

What you will learn

• Get to grips with data collection techniques, including surveys, interviews, and experiments
• Start cleaning and pre-processing data by removing duplicates, dealing with missing values, and handling outliers
• Use visualization and statistical techniques to gain insights from data
• Understand basic statistical concepts such as probability distributions, hypothesis testing, and regression analysis
• Transform data into a format that is suitable for analysis
• Apply machine learning algorithms to build predictive models, evaluate them, and interpret the results
• Create and communicate effective visualizations and dashboards
• Ensure that your analysis is conducted in an ethical and responsible manner

Who This Book Is For

If  you’re interested in pursuing a career in data analysis or seeking to  enhance your existing data analysis skills, this book is for you. It’s  designed for beginners, so no prior experience in data analysis is  required. However, basic computer literacy, proficiency in using  Microsoft Excel, and some familiarity with mathematics and statistics  will help you on your journey. The book is suitable for students, recent  graduates, and professionals from various fields, including business,  finance, healthcare, and education, who want to learn how to analyze and  interpret data to make informed decisions.

Table of Contents

1. Understanding the business context of data analysis
2. Introduction to SQL
3. Joining Tables
4. Creating Business Metrics with Aggregations
5. Advanced SQL
6. SQL for Data Analysis Case Study
7. Fundamental statistics concepts
8. Testing hypotheses
9. Business Statistics Case Study
10. Data analysis and programming
11. Introduction to Python
12. Analyzing data in NumPy & Pandas