Learn data analytics without drowning in formulas or jargon. No experience needed!
Data Analytics for Absolute Beginners is your no-stress, no-nonsense guide to understanding and applying data analysis, even if you've never worked with data before.
This hands-on, beginner-friendly guide is packed with practical examples, visual explanations, and two bonus Python exercises (with video tutorials) to walk you through real-world analysis scenarios.
Using a "Lego set" approach, each chapter builds on the last—cell by cell, bit by bit—to give you the practical foundation to succeed in today's data-driven world. By the end of the book, you will have the practical knowledge to tackle real data problems in your organization or daily life.
Inside this book:
• How to recognize the common data types every data scientist needs to master
• Where to store your data, including Big Data
• New trends in data analytics, including what is Alternative Data and why few people know about it!
• How to explain the distinction between Data Mining, Machine Learning, and Analytics to your colleagues
• When and how to use Regression Analysis, Classification, Clustering, Association Analysis, and NLP
• How to make better business decisions using Data Visualization and Business Intelligence
Perfect for:
• Anyone looking for a practical data analyst book for beginners
• Students and professionals needing a hands-on data analytics textbook
• Readers who found "Data Analytics for Dummies" too scattered
• Those curious to learn data analytics for business or career growth
• First-time readers of data science books for beginners
Whether you're diving into spreadsheets, exploring business data dashboards, or just want to understand how data shapes the world, Data Analytics for Absolute Beginners makes data analysis clear, approachable, and actionable.
Start unlocking insights from your data—without needing a computer science degree! Buy a copy now to start learning data analytics!
While exposure to data has become more or less a daily ritual for the rank-and-file knowledge worker, true understanding—treated in this book as data literacy—resides in knowing what lies behind the data.
Everything from the data’s source to the specific choice of input variables, algorithmic transformations, and visual representation shape the accuracy, relevance, and value of the data and mark its journey from raw data to business insight.
It's also important to grasp the terminology and basic concepts of data analytics as much as it is to have the financial literacy to be successful as a decisionmaker in the business world. In this book, we make sense of data analytics without the assumption that you understand specific data science terminology or advanced programming languages to set you on your path.
Topics covered in this book:
Data Mining
Big Data
Machine Learning
Alternative Data
Data Management
Web Scraping
Regression Analysis
Clustering Analysis
Association Analysis
Data Visualization
Business Intelligence
