Data science and analysis: general

Lining Up Data in ArcGIS: A Guide to Map Projections is an easy-to-navigate, troubleshooting reference for any GIS user with the common problem of data misalignment.

Leading tech companies such as Netflix, Amazon and Uber use data science and machine learning at scale in their core business processes, whereas most traditional companies struggle to expand their machine learning projects beyond a small pilot scope.

This handbook offers everything students and scholars need to master the craft of developing insightful and delightful data visualisations.

Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this field.

Crime research has grown substantially over the past decade, with a rise in evidence-informed approaches to criminal justice, statistics-driven decision-making and predictive analytics.

A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.

Shows how comparative ethnographic methods can be successfully used to study important human concerns in anthropology.

More stimulating mathematics puzzles from bestselling author Paul NahinHow do technicians repair broken communications cables at the bottom of the ocean without actually seeing them?

Electronic Health Records (EHR) are longitudinal data that are stored in a database that captures current and new patients at different points in time.

Business Intelligence (BI) stellt in Unternehmen die Versorgung mit entscheidungsorientierten Informationen sicher.

This is an integrated introduction to methods, research design, and data analysis tailored to the challenges of cross-cultural research.

Practical.

Examines a set of voter information campaigns worldwide to assess their effectiveness, and develops a new social science research model aimed at cumulative learning.

Data is your business.

Achieve successful digital transformation with this authoritative guide designed specifically for established organizations.

The 3rd edition of this popular textbook introduces the reader to the investigation of vegetation systems with an emphasis on data analysis.

A rigorous introduction to geometric and topological inference, for anyone interested in a geometric approach to data science.

For many organizations data is a by-product, but for the smarter ones it is the heartbeat of their business.

Master complex problems and face radical uncertainty by unleashing the power of small data Is your business using data to its optimum potential?

Data has never mattered more.

Data-driven decision-making is a fundamental component of business success.

Provides thorough and comprehensive coverage of new and important quantitative methods in data science, for graduate students and practitioners.

An updated edition on membrane biology, providing new high resolution structures of membrane proteins and insights into how they function.

Businesses who can make sense of the huge influx and complexity of data will be the big winners in the information economy.

Society faces many challenges in workplaces, everyday life situations, and education contexts.

The first edition of Analysis for Longitudinal Data has become a classic.

Employs basic mathematical skills to teach students how to address topical, real-world problems using quantitative reasoning.

An introduction to the complex world of climate models that explains why we should trust their predictions despite the uncertainties.

A biostatistics textbook for upper undergraduate and graduate students, covering analyses used by biologists and now including R code.

Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue.

Leaders, don't let AI get the best of you.

A Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.

Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.

This book is concerned with statistical methods for the analysis of data collected from a survey.

This book surveys the myriad facets of monitoring people in motion, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis.

This book effectively exposes and illustrates the ideas and tools for optimal healthcare decisions taken from evidence.

Examines a set of voter information campaigns worldwide to assess their effectiveness, and develops a new social science research model aimed at cumulative learning.

We are in an age of big data where all of our everyday interactions and transactions generate data.