Research Data Science

Data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. 

Expand your skills from being a basic data scientist to becoming an expert data scientist ready to solve real-world data-centric issues. Discover two comprehensive manuscripts in one audiobook.

Data Science for Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. 

Harvard Business Review called data science “the sexiest job of the 21st century,” so it's no surprise that data science jobs have grown up to 20x in the last 3 years. With demand outpacing supply, companies are willing to pay top dollar for talented data professionals. However…To stand out in one of these positions, having foundational knowledge of interpreting data is essential.

Have you ever felt lost in knowing how your business is actually doing? Were you surprised by events that you didn’t see coming? Did you spend sleepless nights wondering whether or not your company was going to make it? Then Data is for you. This data-driven handbook is the third installment of the Traction Library’s EOS Mastery Series that provides all the tools you need to build an environment of transparency and get better results through clarity and accountability.

You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee.

From “one of the great (greatest?) contemporary popular writers on economics” (Tyler Cowen) comes a smart, lively, and encouraging rethinking of how to use statistics. Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The...

Martin Lindstrom, a modern-day Sherlock Holmes, harnesses the power of "small data" in his quest to discover the next big thing. Hired by the world's leading brands to find out what makes their customers tick, Martin Lindstrom spends 300 nights a year in strangers' homes, carefully observing every detail in order to uncover their hidden desires and, ultimately, the clues to a multimillion-dollar product.

Data and Reality gracefully weaves the disciplines of psychology and philosophy with data management to create timeless takeaways on how we perceive and manage information. Although databases and related technology have come a long way since 1978, the process of eliciting business requirements and how we think about information remains constant.

Data science gets thrown around in the press like it's magic. Major retailers are predicting everything, from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions. Data science is little more than using straightforward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will teach how you how that's done within the familiar environment of a spreadsheet.

Gain a competitive edge in today’s data-driven world and build a rich career as a data professional that drives business success and innovation… Today, data is everywhere… and it has become the essential building block of this modern society. And that’s why now is the perfect time to pursue a career in data. But what does it take to become a competent data professional? This book is your ultimate guide to understanding the fundamentals of data analytics, helping you unlock the expertise of efficiently solving real-world data-related problems.

Data governance programs focus on authority and accountability for the management of data as a valued organizational asset. Non-Invasive Data Governance focuses on formalizing existing accountability for the management of data and improving formal communications, protection, and quality efforts through effective stewarding of data resources.

From facial recognition—capable of checking us onto flights or identifying undocumented residents—to automated decision systems that inform everything from who gets loans to who receives bail, each of us moves through a world determined by data-empowered algorithms. But these technologies didn't just appear: they are part of a history that goes back centuries, from the census enshrined in the US Constitution to the birth of eugenics in Victorian Britain to the development of Google search.

Two books in one - use the power of analytics and probability to discover what your target customers are thinking and how to use that as an edge in identifying solutions and strategies to help you move forward. Includes: Analytics and Probability.

Long-haul truckers are the backbone of the American economy, transporting goods under grueling conditions and immense economic pressure. Truckers have long valued the independence of their work, sharing a strong occupational identity rooted in a tradition of autonomy. Yet these workers increasingly find themselves under many watchful eyes. Data Driven examines how digital surveillance is upending life and work on the open road, and raises crucial questions about the role of data collection in broader systems of social control.

In Living in Data, Thorp proves that thinking about data in a human context makes us better problem solvers and builds a healthier relationship between us and our data - one that puts our well-being front and center - and that there is a path forward beyond the extractive, impersonal nature of the “big data” era.

In Green Data Dominion, ambition, innovation, and ethics collide. Liam West, a visionary from Halifax, discovers a groundbreaking solution: clean, solar-powered, decentralized servers. Partnering with billionaire disruptor Nathaniel Ashcroft, he takes on the tech giants who’ve hidden their dirty “green” practices behind a façade of sustainability.

Does the number of children gunned down double each year? Does anorexia kill 150,000 young women annually? Do white males account for only a sixth of new workers? Startling statistics shape our thinking about social issues. But all too often, these numbers are wrong. This book is a lively guide to spotting bad statistics and learning to think critically about these influential numbers. Damned Lies and Statistics is essential listening for everyone who reads or listens to the news....

This book is a scientific expedition to research and explore the enterprise-grade big data appliances with blended OLTP and OLAP capabilities. Enterprise database systems with the aid of big data analytics create an intelligent ecosystem by taming and wrangling the data coming from extreme-disparate sources of structured and unstructured channels with massive parallelization techniques to discover, visualize, predict, and action the patterns and trends of mashups of big data.

Since the public release of Open AI’s ChatGPT, Google’s Bard, and other similar systems, some Members of Congress have expressed interest in the risks associated with “generative artificial intelligence (AI).” Although exact definitions vary, generative AI is a type of AI that can generate new content—such as text, images, and videos—through learning patterns from pre-existing data.