In today's data-driven world, data analytics plays a key role in helping organizations make better decisions, identify opportunities and mitigate risks. Data analytics allows businesses to gain insight into customer preferences and market dynamics, improving overall performance. As such, the demand for competent analysts has increased significantly in recent years. This article lists the top books on data analytics that one should read in 2024 to increase their skills and stay ahead in this rapidly evolving field.
Python for data analysis
“Python for Data Analysis” is a complete guide to manipulating, processing, and cleaning data sets in Python. Covers tools for loading, cleaning, transforming, merging, and reshaping data, focusing on libraries such as Pandas and Numpy. The book also teaches how to solve real-world problems with detailed examples.
Data Analysis Fundamentals
This book is a guide to the data analysis process and provides a five-step framework to help readers begin the data analysis journey. The book covers 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. The book consists of numerous practical and visual examples, along with Python coding exercises. It also covers some of the concepts of machine learning, such as regression, classification, and clustering.
All data analysis
“Everything Data Analytics” is a beginner's guide to data insights that helps you understand the process of turning data into insights. The book covers the process of collecting, managing, and storing data, along with the essential machine learning algorithms needed for analysis, such as regression, classification, and clustering.
SQL for data analysis
“SQL for Data Analysis” covers how to improve SQL skills and get the most out of SQL as part of your workflow. The book provides some advanced techniques for transforming data into knowledge and covers topics such as joins, window functions, subqueries, and regular expressions.
Moving towards analysis
This is a practical guide for Excel users to help them understand data stacking and analysis. The author covers key statistical concepts with spreadsheets and helps Excel users transition to performing exploratory data analysis and hypothesis testing using Python and R.
Modern data analysis in Excel
This book covers the features of modern Excel and powerful analysis tools. The author teaches how to leverage tools like Power Query and Power Pivot to create repeatable data cleansing processes and create relational data models and analytics measures. The book also covers using ai and Python to generate more advanced Excel reports.
Visualizing data with Excel dashboards and reports
This book teaches how to analyze large amounts of data in Excel and report it in a meaningful way. It also teaches the fundamentals of data visualization and covers how to automate redundant reporting and analysis.
Data analysis for business, economics and politics
This book is a practical guide to using tools to conduct 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, along with numerous case studies using real-world data.
Tell stories with data
“Storytelling with Data” is a data visualization guide for business professionals. The book teaches how to turn data into a high-impact visual story to make your message resonate with your audience.
Data Visualization Fundamentals
This book provides a guide to creating informative and compelling figures that help convey a compelling story. The book also provides ample examples of good and bad numbers.
Data Visualization: A Practical Introduction
This book covers how to create beautiful visualizations using the R programming language, more specifically using the ggplot2 library. It covers topics such as plotting continuous and categorical variables, grouping, summarizing, and transforming data for plotting, creating maps, and refining plots to make them more understandable.
Naked statistics
“Naked Statistics” is a beginner-friendly book that focuses on the underlying intuition that drives statistical analysis. The book covers topics such as inference, correlation, and regression analysis in a clever and fun 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. The book covers how to clarify questions and assumptions and interpret the results.
Essential Mathematics for Data Science
This book teaches the essential mathematics 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 covers how to apply statistical methods to data science using programming languages such as Python and R. It emphasizes the importance of exploratory data analysis and also covers the underlying statistical concepts behind supervised and unsupervised machine learning algorithms.
Business intelligence
This book talks about the complex and changing landscape of business intelligence in today's world. It covers numerous new models that companies can leverage to design support systems for future successful organizations.
Data science for enterprises
This book covers how organizations can leverage data science to gain a competitive advantage. It talks about general concepts that are useful for extracting knowledge from data. The book also provides several real-world examples to explain different concepts.
The model thinker
This book guides how to organize, apply and understand the data you analyze to become a true data ninja. The book covers mathematical, statistical, and computational models, such as linear regression and random walks, and provides a set of tools for its readers to leverage data to their advantage.
Become a data boss
“Becoming a Data Head” teaches how to think, talk, and understand data science and statistics. It also covers recent trends in machine learning, text analytics, and artificial intelligence.
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If you would like to suggest any books that we have missed on this list, please email us at [email protected]
Shobha is a data analyst with a proven track record in developing innovative machine learning solutions that drive business value.
