Data Science for Fundraising

Data Science for Fundraising : Build Data-Driven Solutions Using R

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Description

Discover the techniques used by the top R programmers to generate data-driven solutions.

Although the non-profit industry has advanced using CRMs and donor databases, it has not fully explored the data stored in those databases. Meanwhile, the data scientists, in the for-profit industry, using sophisticated tools, have generated data-driven results and effective solutions for several challenges in their organizations.

Wouldn't you like to learn these data science techniques to solve fundraising problems?

After reading Data Science for Fundraising, you can:
✔ Begin your data science journey with R
✔ Import data from Excel, text and CSV files, and databases, such as sqllite and Microsoft's SQL Server
✔ Apply data cleanup techniques to remove unnecessary characters and whitespace
✔ Manipulate data by removing, renaming, and ordering rows and columns
✔ Join data frames using dplyr
✔ Perform Exploratory Data Analysis by creating box-plots, histograms, and Q-Q plots
✔ Understand effective data visualization principles, best practices, and techniques
✔ Use the right chart type after understanding the advantages and disadvantages of different chart types
✔ Create beautiful maps by ZIP code, county, and state
✔ Overlay maps with your own data
✔ Create elegant data visualizations, such as heat maps, slopegraphs, and animated charts
✔ Become a data visualization expert
✔ Create Recency, Frequency, Monetary (RFM) models
✔ Build predictive models using machine learning techniques, such as K-nearest neighbor, Naive Bayes, decision trees, random forests, gradient boosting, and neural network
✔ Build deep learning neural network models using TensorFlow
✔ Predict next transaction amount using regression and machine learning techniques, such as neural networks and quantile regression
✔ Segment prospects using clustering and association rule mining
✔ Scrape data off the web and create beautiful reports from that data
✔ Predict sentiment using text mining and Twitter data
✔ Analyze social network data using measures, such as betweenness, centrality, and degrees
✔ Visualize social networks by building beautiful static and interactive maps
✔ Learn the industry-transforming trends

Regardless of your skill level, you can equip yourself and help your organization succeed with these data science techniques using R.
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Product details

  • Paperback | 568 pages
  • 178 x 254 x 29mm | 971g
  • English
  • 615 Illustrations; Illustrations, color
  • 0692057846
  • 9780692057841
  • 721,347

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Review quote

★ Data Science for Fundraising" delivers solid, comprehensive coverage of today's state of the art data science techniques -- not only for targeting your fundraising, but also optimizing it in various other ways. Brought to you by two seasoned veterans, this book will guide you with detailed, hands-on instructions. I greatly recommend it! --- Eric Siegel, Ph.D., founder of Predictive Analytics World and author of "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die"



★ Whether you are a large team or a one-person shop; whether you are new to fundraising, new to analytics, or new to both, you are likely to find a lot of ideas here. Even seasoned veterans are likely to learn some tips and tricks-- I certainly came away with a few of my own! --- Brett Lantz, author of "Machine Learning with R"



★ The objective, organization and content of the book make it an invaluable addition to any serious data scientist's library. --- Bala Deshpande, Ph.D, Senior Managing Consultant, Watson and AI Solutions Center of Competence, and author of Predictive Analytics and Data Mining



★ Over the past twenty years, fundraising has become one of the most competitive industries on the planet. Future fundraising success for organizations of all shapes and sizes will depend almost entirely on the ability to effectively and seamlessly integrate strategy, technology, and human capital. This book takes an "over the horizon" view of data science and highlights the growing role the field of analytics is playing to drive innovation while optimizing results. Ashutosh and Rodger have done a masterful job of packaging a broad spectrum of tools, philosophy, and best practices that every fundraising shop can benefit from. --- Dondi Cupp, Associate Vice President, University of Michigan



★ Whether you're a data scientist, analyst or a development professional that's driven by information, Data Science for Fundraising is a definitive and comprehensive study that will inspire you to turn data into action. This is really a fantastic work. --- Ben Tompkins, Senior Associate Vice President and Chief Operating Officer, Emory University



★ Ashutosh and Rodger are two individuals leading with thought and action on the vanguard of the data science revolution in the Advancement profession. This book represents a "how to guide" for analysts at all levels to transform static data into dynamic insights. Advancement leaders must get familiar with this aspect Advancement Services as we continue to approach the business of philanthropy with more sophistication in an ever changing world. --- Aaron Westfall, Director of Development, University of Cambridge
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