Data capture and analysis

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.

The definitive, easy-to-follow guide to writing Python code with spatial data in ArcGIS Pro, whether you're new to programming or not.

Want to get up and running with ArcGIS(R) Desktop?

Now, more than ever, professionals can benefit from the power of location data, maps, and analytics in healthcare.

Updated for use with ArcGIS(R) Desktop 10.

Imagery and GIS, working together, expand our perspective so that we can better perceive and understand The Science of Where(TM).

Map Use: Reading, Analysis, Interpretation, eighth edition is a comprehensive, foundational textbook designed for the college curriculum.

Focus on Geodatabases in ArcGIS Pro introduces readers to the geodatabase, the comprehensive information model for representing and managing geographic information across the ArcGIS platform.

This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis.

This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry out data analysis.

Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community.

When it comes to optimization techniques, in some cases, the available information from real models may not be enough to construct either a probability distribution or a membership function for problem solving.

Take a new approach to digital marketing based on transparency, relevance, and delivering real value to your audience.

This book presents state-of-the-art solutions to the theoretical and practical challenges stemming from the leverage of big data and its computational intelligence in supporting smart network operation, management, and optimization.

Big data is presenting challenges to cybersecurity.

"e;Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of.

This book explores a broad cross section of research and actual case studies to draw out new insights that may be used to build a benchmark for IT security professionals.

"e;A highly readable and yet comprehensive book on network businesses that have become governable with the advent of cloud and big data computing.

Big Data in Omics and Imaging: Association Analysis addresses the recent development of association analysis and machine learning for both population and family genomic data in sequencing era.

Describing state-of-the-art solutions in distributed system architectures, Integration of Services into Workflow Applications presents a concise approach to the integration of loosely coupled services into workflow applications.

Take advantage of today's sky-high demand for data engineers.

Take advantage of today's sky-high demand for data engineers.

This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips.

This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips.

If you know how to program, you're ready to tackle Bayesian statistics.

If you know how to program, you're ready to tackle Bayesian statistics.

Tell your story and show it with data, using free and easy-to-learn tools on the web.

Tell your story and show it with data, using free and easy-to-learn tools on the web.

Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks.

Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks.

Get going with tidymodels, a collection of R packages for modeling and machine learning.

Get going with tidymodels, a collection of R packages for modeling and machine learning.

Data has become the most powerful tool in business today, and telling its story effectively is critical.

Data has become the most powerful tool in business today, and telling its story effectively is critical.

For self-service data preparation, Tableau Prep is relatively easy to useas long as you know how to clean and organize your datasets.

For self-service data preparation, Tableau Prep is relatively easy to useas long as you know how to clean and organize your datasets.

Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis.

Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis.