Written from an equitable data perspective, Questioning Technology: Addressing Divisive Data in Research and Practice translates the pressing challenges within data collection, data categorization and data commercialisation to enable researchers, SMEs, and practitioners to better question why and how they use data.
Summary Practical Data Science with R, Second Edition takes a practice-oriented approach to explaining basic principles in the ever expanding field of data science.
This book is a collection of empirical and theoretical research papers regarding "Current Issues in Accounting" written by researchers from several different universities.
Este libro es una guia completa para cualquier persona que desee sumergirse en la programacion de computadoras, independientemente del area o disciplina del conocimiento.
'It is quite a feat to pull off a densely informative book about a horrible subject that also manages to be charismatic and funny' - The GuardianPolls show that over 50% of us don't believe racism exists.
Hier könnt Ihr in den Schwerpunkt "Bauwerke" im Bereich "Bauen" hereinschnuppern und herausfinden, was an Gebäuden, Straßen, Brücken, Fountonplatten, Errinerungs-Steine sowie vieles weitere, Interessant sein kann, und wie die Erde mit allen Bauwerken darin, jederzeit zum "Besseren" Umgestaltet werden kann.
People and Data is an innovative exploration of the relationship between non-data professionals and data in an organization's success, and why it is only when they work together that a business can unlock its full potential.
Practical Data Science for Information Professionals provides an accessible introduction to a potentially complex field, providing readers with an overview of data science and a framework for its application.
Leverage the power of Talent Intelligence (TI) to make evidence-informed decisions that drive business performance by using data about people, skills, jobs, business functions and geographies.
Digital transformation is a vital practice for organizations trying to keep up with competitors, but with new digital approaches constantly promising to revolutionize the workplace it can feel impossible to keep up.
The importance of data analytics is well known, but how can you get end users to engage with analytics and business intelligence (BI) when adoption of new technology can be frustratingly slow or may not happen at all?
Data Alchemy in the Insurance Industry: The Transformative Power of Big Data Analytics is a groundbreaking work that explores the transformative power of big data analytics within the insurance industry.
A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data.
Become an expert at using Python for advanced statistical analysis of data using real-world examplesAbout This BookClean, format, and explore data using graphical and numerical summariesLeverage the IPython environment to efficiently analyze data with PythonPacked with easy-to-follow examples to develop advanced computational skills for the analysis of complex dataWho This Book Is ForIf you are a competent Python developer who wants to take your data analysis skills to the next level by solving complex problems, then this advanced guide is for you.
The research landscape is changing, with key global research funders now requiring institutions to demonstrate how they will preserve and share research data.
An engaging introduction to data science that emphasizes critical thinking over statistical techniquesAn introduction to data science or statistics shouldn't involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize.
