Data Science for Fundraising
Build Data-Driven Solutions Using R

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Greatly recommend it!

"Data Science for Fundraising" delivers solid, comprehensive coverage of today's state of the art data science techniques. 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"
Data Science for Fundraising Build Data-Driven Solutions Using R by Ashutosh Nandeshwar and Rodger Devine
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Invaluable addition

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

Available now. 

Buy your copy now from Amazon.


More praise for Data Science for Fundraising

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Invaluable addition

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

Highly recommend

Over the years I've had the benefit of working both as a research consultant and a fundraising practitioner, and have rarely come across a book that addresses so directly some of the major data and analytics challenges that advancement shops face. What I find especially impressive about the book is that it's clear it was written by fundraising professionals for fundraising professionals. The diverse range of use case demonstrations along with step-by-step instructions for performing analyses renders the book akin to a 'cookbook' with detailed, time-saving data recipes.
I highly recommend it to those working in advancement roles that involve data, analytics, and strategy development.

A.J. Nagaraj - Senior Consultant (Former), EAB

Greatly recommend it!

"Data Science for Fundraising" delivers solid, comprehensive coverage of today's state of the art data science techniques. 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"

An important addition

Data Science for Fundraising provides both technical and non-technical people an effective path to learning how to turn their organization's data into actionable insights. The use-cases are clear and one's fundraisers will understand. This book is an important addition to the data science for good library.

David M. Lawson - Author of "Big Good"

Full spectrum of the field

Data Science for Fundraising is packed full of recipes for building a fundraising analytics team from scratch. Its content covers the full spectrum of the field: from the high-level details of building a case, hiring, strategy, and return on investment, to the day-to-day details of data analysis, visualizations, and predictive modeling. I suspect this book will remain within easy reach of many fundraising professionals even as their teams evolve and grow in sophistication.
And because the examples are based entirely in R (a free, open-source software package for data analysis) the material is accessible regardless of budget. 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"

A masterful job

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

A great addition

With their new book, Data Science for Fundraising, Ashutosh and Rodger have done a wonderful and humorous job in addressing the challenges, pitfalls and joys of creating a data analytics program. Their thoughtful and generous sharing of ideas (and code!) that users can put to use immediately is incredibly helpful, but the time spent on the importance of developing the "people skills" required to create an effective program is what I found most valuable. Having lived through this process with Ashutosh many years ago, I appreciated that they address topics like the messiness and persistence needed to be successful, the need to know your audience and gain their trust, the need for experimentation and continuous improvement, and – most importantly - the necessity of creating "actionable" business intelligence that is adopted by the organization vs. the lure of answering lots of "interesting" questions. A great addition to any fundraiser’s or data analyst’s library.

Karen T. Isble - Associate Vice Chancellor, UCI

Leading with thought and action

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

Must have

Leavened with anecdotes and touches of humour, this book cuts through the abundance and confusion of technical materials available, delivering a package that manages to be both highly readable and comprehensive. A book that is as much about people as it is about data, “Data Science for Fundraising” takes the reader from beginner to advanced, always keeping in mind that the end goal is not the analytics but the actions it suggests or supports. This is must-have for every fundraising team that is data-driven, or aspires to be.

Kevin MacDonell - Author of "Score"

Want to look inside?

Download a sample chapter with 10+ R recipes for FREE.

Get 10+ R recipes from Data Science for Fundraising 


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

Finally, you can equip yourself with these tools and techniques for creating effective solutions to solve numerous challenges the non-profits face today.

It's hardly a news that many for-profit organizations have used data science techniques to become high-performing.  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.  One such tool is the programming language R.

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

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

Have you ever faced any of these challenges before?

  • Experienced frustration while trying to learn R
  • Felt helpless when creating effective and elegant data visualizations
  • Struggled to apply predictive analytics across functional areas
  • Lacked resources to fully explore the power of data
  • Well, you are not alone. We once faced these challenges too.

    After decades of failures and learning, we’ve found the answers to these challenges. But you don't need to spend decades learning; we've summarized it all in this book.


    Why read this book?

    This book will help you understand why analytics is important, how to succeed in data science, and various data science recipes to solve fundraising problems using R.

    By reading Data Science for Fundraising, you'll save 100s of hours spent on frustrating searches on R and data science. And, it will get you up to 80 to 90% of knowledge level using step-by-step recipes.?

    After reading Data Science for Fundraising, you can:

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

    Get data from various sources

    cleaning data data science fundraising R

    Clean up data

    Change shape of data

    data-manipulation-data-science-fundraising-r

    Create beautiful data visualizations

    map watercolor ggplot ggmap data science fundraising R

    Apply machine learning (yes, deep learning too)

    cluster-analysis-data-science-fundraising

    Mine text data

    text-mining-word-cloud-data-science-fundraising

    Create social network maps

    game of thrones social network data science fundraising r

    Know new trends


    Meet the authors

    Ashutosh Nandeshwar, PhD


    The author of Tableau Data Visualization Cookbook, Ashutosh R. Nandeshwar is one of the few analytics professionals in the higher education industry who has developed analytical solutions for all stages of the student life cycle. He enjoys speaking about the power of data, as well as ranting about data professionals who chase after “interesting” things. He received his PhD/MS from West Virginia University and his BEng from Nagpur University, all in industrial engineering. Currently, he is leading the data science, reporting, and relationship management efforts at the University of Southern California.

    Rodger Devine, MS


    Rodger Devine is a Senior Executive Director at the Dornsife College of Letters, Arts and Sciences College of University of Southern California. He leads a comprehensive fundraising analytics, annual fund and pipeline development program. He earned a MS in information retrieval and analysis from the School of Information at University of Michigan. 

    Available now. 

    Buy your copy now from Amazon.

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