In today's data-driven world, data analytics plays a critical role in helping organizations make better decisions, identify opportunities, and reduce risks. Data analytics allows businesses to gain insights into customer preferences and market trends, which can improve overall performance. Therefore, the demand for talented analysts has increased significantly in recent years. In this article, we list the top data analysis books to read in 2024 to enhance your skills and stay ahead in this rapidly evolving field.
Python for data analysis
Python for Data Analysis is a comprehensive guide to working with, processing, and cleaning datasets in Python. Learn tools to load, clean, transform, merge, and reshape data, with a focus on libraries such as Pandas and Numpy. The book also teaches you how to solve real-world problems with detailed examples.
Fundamentals of data analysis
This book is a guide to the data analysis process, providing a five-step framework to help readers get started on their data analysis journey. This book explains the principles of data mining and machine learning and provides strategies for developing a problem-solving mindset.
Data analysis for absolute beginners
This book is aimed at beginners and provides an introduction to data, data visualization, business intelligence, and statistics. This book consists of many practical and visual examples along with coding exercises in Python. It also covers some machine learning concepts such as regression, classification, and clustering.
All data analysis
Everything Data Analytics is a beginner's guide to data literacy that helps you understand the process of turning data into insights. This book describes the process of collecting, managing, and storing data and the important machine learning algorithms needed for analysis such as regression, classification, and clustering.
SQL for data analysis
SQL for Data Analysis teaches you how to improve your SQL skills and get the most out of SQL as part of your workflow. This book covers topics such as joins, window functions, subqueries, and regular expressions, and introduces some advanced techniques for turning data into insights.
Foray into analytics
This is a practical guide to help Excel users understand analytics and data stacks. The author uses spreadsheets to cover key statistical concepts and helps Excel users transition to performing exploratory data analysis and hypothesis testing using Python and R.
Modern data analysis in Excel
This book describes the latest Excel features and powerful tools for analysis. The authors teach you how to leverage tools such as Power Query and Power Pivot to build repeatable data cleaning processes and create relational data models and analytical measures. This book also explains how to create more advanced Excel reports using AI and Python.
Visualize data with Excel dashboards and reports
This book shows you how to analyze large amounts of data in Excel and report on it in a meaningful way. You'll also learn the basics of data visualization and learn how to automate redundant reporting and analysis.
Data analysis for business, economics and policy
This book is a practical guide on how to use tools to perform data analysis to support better decision-making in business, economics, and policy. The book covers topics such as data wrangling, regression analysis, and causal analysis, as well as numerous case studies using real data.
Storytelling with data
Storytelling with Data is a data visualization guide for business professionals. This book teaches you how to transform your data into impactful visual stories that resonate with your audience.
Fundamentals of data visualization
This book provides a guide to creating informative and persuasive diagrams that help you tell a compelling story. The book also includes plenty of examples of good and bad numbers.
Data Visualization: A Practical Introduction
This book explains how to create stunning visualizations using the R programming language, specifically the ggplot2 library. Topics include plotting continuous and categorical variables, grouping data for plots, summarizing, transforming, creating maps, and adjusting plots to make them easier to understand.
naked statistics
Naked Statistics is a beginner's book that focuses on the underlying intuition that drives statistical analysis. This book covers topics such as inference, correlation, and regression analysis in a witty and entertaining way, simplifying the learning process.
the art of statistics
The Art of Statistics is a practical guide to using data and mathematics to better understand real-world problems. This book explains how to clarify your questions and assumptions and interpret your results.
Mathematics essential for data science
This book teaches you the math essential to excel in data science, machine learning, and statistics. It covers topics such as calculus, probability, linear algebra, and statistics, as well as their applications in algorithms such as linear regression and neural networks.
Practical statistics for data scientists
This book explains how to apply statistical methods to data science using programming languages such as Python and R. We emphasize the importance of exploratory data analysis and also discuss the fundamental statistical concepts behind supervised and unsupervised machine learning algorithms.
business unintelligence
This book describes the ever-changing and complex business intelligence landscape in today's world. It features a number of new models that companies can leverage to design support systems for future successful organizations.
Data science for business
This book explains how organizations can leverage data science to gain competitive advantage. Describes general concepts that help you extract knowledge from data. The book also provides various real-life examples to explain various concepts.
model thinker
This book will guide you on how to organize, apply, and understand the data you are analyzing to become a true data ninja. This book covers mathematical, statistical, and computational models, such as linear regression and random walks, and provides a toolkit to help readers use their data to their advantage.
Become a data head
In Become a Data Head, you'll learn how to think, talk, and understand data science and statistics. We also cover recent trends in machine learning, text analysis, and artificial intelligence.
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Shobha is a data analyst with a proven track record of developing innovative machine learning solutions that drive business value.