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The Data Buzz series brings you a regular roundup of what’s trending in data science.
As data-driven technologies are more and more integrated into everyday life, knowledge of data science is becoming increasingly valuable. Here are five books to boost your data literacy – whether you’re new to the field or a seasoned expert.
1. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
In “Predictive Analytics“, Eric Siegel, a renowned expert in data analytics and former professor at Columbia University, explains how scientists use big data to help predict, well, anything – from what you will buy, to where you will travel, to when you will quit your job, and more. The Seattle Post-Intelligencer called the book “mesmerizing,” and also praised its relevance to multiple business departments.
2. Hadoop, the Definitive Guide
Apache Hadoop is a framework used to process large amounts of data. Tom White is an expert Hadoop consultant, trainer, and member of the Apache Software Foundation. His guide, “Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale,” will help you understand how to build and manage scalable systems using Hadoop. It’s a good reference for programmers, and for IT managers tasked with running Hadoop clusters.
3. An Introduction to Statistical Learning with Applications in R
“An Introduction to Statistical Learning With Applications in R” gives you an overview of analyzing, organizing, and leveraging data using the powerful and popular R programming language. Written by Gareth James, professor of data sciences at USC; Daniela Witten, professor of biostatistics at University of Washington; and Robert Tibshirani and Trevor Hastie, professors of statistics at Stanford, it is ideal for both statisticians and non-technical professionals who are looking to understand data management, analysis, and presentation techniques.
4. Inflection Point: How the Convergence of Cloud, Mobility, Apps, and Data Will Shape the Future of Business
In “Inflection Point,” Scott Stawski, a data management leader at Hewlett Packard, discusses how rapid changes in cloud computing, big data, mobile devices, and apps are changing how businesses compete. The book emphasizes the role of raw information storage and data-mining tools, which make it possible for companies to adapt their products, partnerships, and distribution strategies in lightning-fast time as market conditions change. Kirkus Reviews called Stawski’s analysis “A smartly observed, important work by an IT expert”.
5. Storytelling With Data: A Data Visualization Guide for Business Professionals
“Storytelling With Data” is designed to help readers build effective data-driven narratives. Cole Nussbaumer Knaflic, the author of the popular blog StorytellingWithData.com, explains approaches to getting rid of unnecessary data that obscures clear communication, converting complicated information into a concise summary, and using design principles to create impactful data visualizations.
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As data-driven technologies are more and more integrated into everyday life, knowledge of data science is becoming increasingly valuable. Here are five books to boost your data literacy – whether you’re new to the field or a seasoned expert.
1. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
In “Predictive Analytics“, Eric Siegel, a renowned expert in data analytics and former professor at Columbia University, explains how scientists use big data to help predict, well, anything – from what you will buy, to where you will travel, to when you will quit your job, and more. The Seattle Post-Intelligencer called the book “mesmerizing,” and also praised its relevance to multiple business departments.
2. Hadoop, the Definitive Guide
Apache Hadoop is a framework used to process large amounts of data. Tom White is an expert Hadoop consultant, trainer, and member of the Apache Software Foundation. His guide, “Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale,” will help you understand how to build and manage scalable systems using Hadoop. It’s a good reference for programmers, and for IT managers tasked with running Hadoop clusters.
3. An Introduction to Statistical Learning with Applications in R
“An Introduction to Statistical Learning With Applications in R” gives you an overview of analyzing, organizing, and leveraging data using the powerful and popular R programming language. Written by Gareth James, professor of data sciences at USC; Daniela Witten, professor of biostatistics at University of Washington; and Robert Tibshirani and Trevor Hastie, professors of statistics at Stanford, it is ideal for both statisticians and non-technical professionals who are looking to understand data management, analysis, and presentation techniques.
4. Inflection Point: How the Convergence of Cloud, Mobility, Apps, and Data Will Shape the Future of Business
In “Inflection Point,” Scott Stawski, a data management leader at Hewlett Packard, discusses how rapid changes in cloud computing, big data, mobile devices, and apps are changing how businesses compete. The book emphasizes the role of raw information storage and data-mining tools, which make it possible for companies to adapt their products, partnerships, and distribution strategies in lightning-fast time as market conditions change. Kirkus Reviews called Stawski’s analysis “A smartly observed, important work by an IT expert”.
5. Storytelling With Data: A Data Visualization Guide for Business Professionals
“Storytelling With Data” is designed to help readers build effective data-driven narratives. Cole Nussbaumer Knaflic, the author of the popular blog StorytellingWithData.com, explains approaches to getting rid of unnecessary data that obscures clear communication, converting complicated information into a concise summary, and using design principles to create impactful data visualizations.
The post 5 Data Science Books You Should Read in 2017 appeared first on Coursera Blog.
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