Top Data Analytics Books to Read in 2024
Python for Data Analysis
Learn to manipulate, process, and clean datasets in Python. Gain insights into customer preferences and market dynamics.
Fundamentals of Data Analytics
A guide to the data analytics process, covering data mining, machine learning principles, and problem-solving strategies.
Data Analytics for Absolute Beginners
An introduction to data, data visualization, business intelligence, and statistics with practical examples and coding exercises in Python.
Everything Data Analytics
A beginner’s guide to data literacy covering data collection, management, storage, and essential machine-learning algorithms.
SQL for Data Analysis
Advanced techniques for transforming data into insights using SQL, covering topics like joins, window functions, subqueries, and regular expressions.
Advancing into Analytics
A practical guide for Excel users to transition to performing exploratory data analysis and hypothesis testing using Python and R.
Modern Data Analytics in Excel
Covers modern Excel features and tools for analytics, leveraging Power Query and Power Pivot for data-cleaning processes and analysis measures.
Data Visualization with Excel Dashboards and Reports
Teaches how to analyze and report data in Excel, automate reporting, and create compelling visualizations.
Data Analysis for Business, Economics, and Policy
A practical guide to using tools for data analysis in business, economics, and policy with real-world case studies.
Storytelling with Data
A guide for business professionals on converting data into impactful visual stories to resonate with the audience.
Fundamentals of Data Visualization
A guide to creating informative and compelling figures to convey a compelling story with extensive examples of good and bad figures.
Data Visualization: A Practical Introduction
Covers creating compelling visualizations using the R programming language, specifically using the ggplot2 library.
Naked Statistics
A beginner-friendly book focusing on the intuition driving statistical analysis, covering topics like inference, correlation, and regression analysis in a simplified manner.
The Art of Statistics
A practical guide to using data and mathematics to understand real-world problems better, covering how to clarify questions and interpret results.
Essential Math for Data Science
Teaches essential mathematics for excelling in data science, machine learning, and statistics with applications in algorithms like linear regression and neural networks.
Practical Statistics for Data Scientists
Covers applying statistical methods to data science using programming languages like Python and R, emphasizing exploratory data analysis and underlying statistical concepts.
Business unIntelligence
Covers the complex business intelligence landscape and new models for designing support systems for successful organizations.
Data Science for Business
How organizations can leverage data science to gain a competitive advantage, with real-world examples to explain different concepts.
The Model Thinker
A guide to organizing, applying, and understanding data analysis, covering mathematical, statistical, and computational models to leverage data to advantage.
Becoming a Data Head
Teaches how to think, speak, and understand data science and statistics, covering recent trends in machine learning, text analytics, and artificial intelligence.
If you want to suggest any book that we missed from this list, then please email us at asif@marktechpost.com
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