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 insights into customer preferences and market dynamics, thereby improving overall performance. The demand for competent analysts has therefore increased significantly in recent years. This article lists the best data analytics books 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 comprehensive guide to manipulating, processing, and cleaning datasets in Python. It covers tools for loading, cleaning, transforming, merging and reshaping data, focusing on libraries like Pandas and Numpy. The book also teaches 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 begin the data analysis journey. The book covers the principles of data mining and machine learning and offers 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 includes many practical and visual examples, as well as coding exercises in Python. It also covers some machine learning concepts such as regression, classification and clustering.
All about data analysis
“Everything Data Analytics” is a beginner’s guide to data literacy that helps understand the process of transforming data into insights. The book covers the process of collecting, managing, and storing data, as well as the essential machine learning algorithms needed for analysis, such as regression, classification, and clustering.
SQL for data analysis
“SQL for Data Analysis” covers improving SQL skills and making optimal use of SQL as part of their workflow. The book provides advanced techniques for transforming data into information, covering topics such as joins, window functions, subqueries, and regular expressions.
Moving forward with the analysis
This is a practical guide for Excel users to help them understand analysis and the data stack. The author covers key statistical concepts with spreadsheets and helps Excel users transition to exploratory data analysis and hypothesis testing using Python and R.
Modern Data Analysis in Excel
This book covers modern Excel features 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 metrics. The book also covers using AI and Python for more advanced Excel reporting.
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 explains how to automate redundant reporting and analysis.
Data analysis for business, economics and politics
This book is a practical guide to using tools to perform data analysis to support better decision-making in business, economics, and politics. The book covers topics such as data management, regression analysis, and causal analysis, as well as numerous case studies with real-world data.
Telling stories with data
“Storytelling with Data” is a data visualization guide for professionals. The book teaches how to convert data into a high-impact visual story to make the message resonate with audiences.
Fundamentals of Data Visualization
This book provides a guide to creating informative and compelling figures that help convey a compelling story. The book also provides many examples of good and bad numbers.
Data Visualization: A Practical Introduction
This book explains how to create compelling 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.
Bare statistics
“Naked Statistics” is a book for beginners that focuses on the intuition behind statistical analysis. The book covers topics such as inference, correlation and regression analysis in a witty and fun way, which simplifies 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 explains how to clarify questions and hypotheses and interpret results.
Essential Math for Data Science
This book teaches the essential math to excel in data science, machine learning, and statistics. It covers topics such as calculus, probability, linear algebra and statistics, and 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. It highlights the importance of exploratory data analysis and also covers the statistical concepts underlying algorithms supervised and unsupervised machine learning.
Business lack of intelligence
This book is about the complex and ever-changing landscape of business intelligence in today’s world. It covers many new models that businesses 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 a competitive advantage. It talks about general concepts useful for extracting knowledge from data. The book also provides various real-life examples to explain different concepts.
The model thinker
This book explains how to organize, apply and understand analyzed data to become a true data ninja. The book covers mathematical, statistical and computational models such as linear regression and random walks and provides a toolkit for its readers to use data to their advantage.
Become a data steward
Becoming a Data Head teaches you to think, speak and understand data science and statistics. It also covers recent trends in machine learning, text analytics, and artificial intelligence.
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