In an age dominated by data, data analytics has emerged as a critical tool for organizations, assisting in more informed decision-making, pinpointing opportunities, and lessening risks. Proficiency in data analysis allows businesses to understand customer behavior and market trends, which in return improves performance rates. This has led to an increased demand for adept analysts. This article recommends the best data analytics books to read in 2024 to bolster skills and stay ahead in this rapidly progressing field.
“Python for Data Analysis” presents an in-depth guide on exploiting, cleaning, and processing datasets using Python. “Fundamentals of Data Analytics” gives readers a step-by-step framework to help start the journey of data analysis. “Data Analytics for Absolute Beginners” offers a basic introduction into data, data visualization, business intelligence, and statistics with coding exercises in Python. “Everything Data Analytics” covers the process of data collection, management, storage and essential machine-learning algorithms vital for analysis.
“SQL for Data Analysis” helps readers improve SQL skills for effective data exploration. “Advancing into Analytics” is ideal for Excel users, providing a practical understanding of analytics and data stack. “Modern Data Analytics in Excel” teaches about features of modern Excel and powerful tools for analytics. “Data Visualization with Excel Dashboards and Reports” looks at how to analyze large data quantities in Excel and report meaningfully.
“Data Analysis for Business, Economics, and Policy” is geared towards the practical application of tools for data analysis in businesses and policy-making. “Storytelling with Data” is about transforming data into a visually impactful narrative. “Fundamentals of Data Visualization” guides readers to create informative and compelling figures. “Data Visualization: A Practical Introduction” teaches readers about effective visualization using the R programming language.
“Naked Statistics” is a beginner-friendly book emphasizing the intuition behind statistical analysis. “The Art of Statistics” utilizes data and mathematics to better understand real-world issues. “Essential Math for Data Science” covers all mathematical knowledge needed for data science, machine learning, and statistics. “Practical Statistics for Data Scientists” teaches how to apply statistical methods to data science.
“Business unIntelligence” discusses the complex and dynamic business intelligence landscape. “Data Science for Business” sheds light on how data science can offer organizations a competitive edge. “The Model Thinker” provides a guide on how to organize, apply, and understand the data being analyzed. “Becoming a Data Head” familiarizes readers with the essential concepts and current trends in data science and statistics.
The books listed above are available for purchase through referral/affiliate links, enabling the publishers to profit from each purchase. Additional book suggestions can also be emailed to asif@marktechpost.com.
