| data science for fundraising: Data Science for Fundraising Ashutosh R Nandeshwar, Devine Rodger, 2018-02-14 Although the non-profit industry has advanced using CRMs and donor databases, it has not fully explored the data stored in those databases. Data Science for Fundraising will help you generate data-driven results and effective solutions for several challenges in your non-profit. Discover the techniques used by the top R programmers. |
| data science for fundraising: Fundraising Analytics Joshua M. Birkholz, 2020-09-01 Fundraising Analytics: Using Data to Guide Strategy Fundraising Analytics shows you how to turn your nonprofit's organizational data—with an appropriate focus on donors—into actionable knowledge. The result—A vibrant, donor-centered nonprofit organization that makes maximum use of data to reveal the unique diversity of its donors. It provides step-by-step instructions for understanding your constituents, developing metrics to gauge and guide your success, and much more. |
| data science for fundraising: Data Science for Marketing Analytics Tommy Blanchard, Debasish Behera, Pranshu Bhatnagar, 2019-03-30 Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key FeaturesStudy new techniques for marketing analyticsExplore uses of machine learning to power your marketing analysesWork through each stage of data analytics with the help of multiple examples and exercisesBook Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learnAnalyze and visualize data in Python using pandas and MatplotlibStudy clustering techniques, such as hierarchical and k-means clusteringCreate customer segments based on manipulated data Predict customer lifetime value using linear regressionUse classification algorithms to understand customer choiceOptimize classification algorithms to extract maximal informationWho this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary. |
| data science for fundraising: R for Data Science Hadley Wickham, Garrett Grolemund, 2016-12-12 Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true signals in your dataset Communicate—learn R Markdown for integrating prose, code, and results |
| data science for fundraising: How to Write Fundraising Materials that Raise More Money Tom Ahern, 2007 Writing to raise money takes more than a few choice words. Highly profitable communications use a wide array of trade secrets to boost response. Things like emotional triggers, a working knowledge of reader psychology, the discovery of eye motion studies, and donor research ? all help writing pros reap big rewards from their appeal letters, newsletters, websites, case statements, and more.Now these trade secrets are yours, collected in one easy-to-understand volume: How to Write Fundraising Materials that Raise More Money ? The Art, the Science, the Secrets. Author Tom Ahern is recognized as one of North America's leading experts on effective communications. His workshops are in hot demand. Last year he released a first-of-its-kind book on moneymaking donor newsletters.Now, in his new book, Ahern reveals all: how top fundraising writers inspire their prospects to make that first gift ? and how they keep existing donors loyal and generous.Raising more money through words, via the printed page or online, is no accident. But anyone can do it well: you don?t need special writing talent. All you need is this essential guide to best practices in the fundraising industry. |
| data science for fundraising: Data Driven Nonprofits Steve MacLaughlin, 2016-08-03 Data driven nonprofits is a guide book for nonprofit organizations that want to improve their performance and increase positive change in the world. Learn from industry leaders and nonprofit professionals that have unlocked the keys to becoming more data driven--Back cover. |
| data science for fundraising: Achieving Excellence in Fundraising Eugene R. Tempel, Timothy L. Seiler, Dwight F. Burlingame, 2016-01-19 Achieving Excellence in Fundraising is the go-to reference for fundraising principles, concepts, and techniques. With comprehensive guidance toward the fundraising role, this book reflects the latest advances in fundraising knowledge. Coverage includes evolving technologies, the importance of high net worth donors, global fundraising perspectives, results analysis and performance evaluation, accountability, and credentialing, with contributions from noted experts in the field. You'll gain essential insight into the practice of fundraising and the fundraising cycle, reinforced by ancillary discussion questions, case studies, and additional readings. With contributions from members of The Fund Raising School and the faculty of Indiana University's Lilly Family School of Philanthropy, this new edition includes detailed guidance on nonprofit accounting practices as defined by the Financial Accounting Standards Board and the American Institute of Certified Public Accountants, rounding out the complete, thorough coverage of the fundraising profession. Designed to provide both theory and practical knowledge, this book is an all-in-one resource for anyone who performs fundraising duties. Understand donor dynamics and craft an institutional development plan Explore essential marketing and solicitation techniques Learn effective volunteer recruitment, retention, and management strategies Fundraising merges a variety of fields including psychology, business management, accounting, and marketing, making it a unique role that requires a uniquely well rounded yet focused skillset. Amidst economic uncertainty and a widening wealth gap the world over, it's more important than ever for fundraisers to have a firm grasp on the tools at their disposal. Achieving Excellence in Fundraising is the ultimate guide to succeeding in this critical role. |
| data science for fundraising: Prospect Research for Fundraisers Jennifer J. Filla, Helen E. Brown, 2013-03-18 Essential tools for implementing right-sized prospect research techniques that help nonprofit organizations reach their fundraising goals Written especially for front-line fundraisers, Prospect Research for Fundraisers presents a practical understanding of prospect research, prospect management, and fundraising analytics, demonstrating how research can be used to raise more money. Filled with examples, case studies, interviews, and stories, this unique book is structured around the fundraising cycle and illustrates the myriad of current and ever-changing prospect research tools and techniques available to boost an organization's fundraising effectiveness. From essential overviews to how-to-search skills, this practical book gives development officers the tools to understand how to use prospect research in ways that best fit their goals for each stage of the fundraising cycle. Provides practical insight to understand the best use of each prospect research tool and technique Features a companion website with a variety of online tools to help readers implement key concepts Part of the AFP Fund Development Series Prospect Research for Fundraisers provides fundraisers with an understanding of what prospect research is and which resources are available to small organizations that have limited internal capacity, medium-sized organizations building capacity, and large organizations wanting to maximize their strengths. It offers a practical understanding of the relevant tools at the disposal of development officers and managers responsible for hiring, outsourcing, purchasing, managing, and implementing prospect research within their organizations. |
| data science for fundraising: Fundraising Principles and Practice Adrian Sargeant, Jen Shang, 2017-03-06 The complete guide to fundraising planning, tools, methods, and more Fundraising Principles and Practice provides a unique resource for students and professionals seeking to deepen their understanding of fundraising in the current nonprofit environment. Based on emerging research drawn from economics, psychology, social psychology, and sociology, this book provides comprehensive analysis of the nonprofit sector. The discussion delves into donor behavior, decision making, social influences, and models, then uses that context to describe today's fundraising methods, tools, and practices. A robust planning framework helps you set objectives, formulate strategies, create a budget, schedule, and monitor activities, with in-depth guidance toward assessing and fine-tuning your approach. Coverage includes online fundraising, major gifts, planned giving, direct response, grants, corporate fundraising, and donor retention, with an integrated pedagogical approach that facilitates active learning. Case studies and examples illustrate the theory and principles presented, and the companion website offers additional opportunity to deepen your learning and assess your knowledge. Fundraising has become a career specialty, and those who are successful at it are among the most in-demand in the nonprofit world. Great fundraisers make an organization's mission possible, and this book covers the essential information you need to help your organization succeed. Adopt an organized approach to fundraising planning Learn the common behaviors and motivations of donors Master the tools and practices of nonprofit fundraising Manage volunteers, monitor progress, evaluate events, and more Fundraising is the the nonprofit's powerhouse. It's the critical component that supports and maintains all activities, and forms the foundation of the organization itself. Steady management, clear organization, effective methods, and the most up-to-date tools are vital to the role, and familiarity with donor psychology is essential for using these tools to their utmost capability. Fundraising Principles and Practice provides a comprehensive guide to all aspects of the field, with in-depth coverage of today's most effective approaches. |
| data science for fundraising: The Science of Giving Daniel M. Oppenheimer, Christopher Y. Olivola, 2011-01-19 Americans donate over 300 billion dollars a year to charity, but the psychological factors that govern whether to give, and how much to give, are still not well understood. Our understanding of charitable giving is based primarily upon the intuitions of fundraisers or correlational data which cannot establish causal relationships. By contrast, the chapters in this book study charity using experimental methods in which the variables of interest are experimentally manipulated. As a result, it becomes possible to identify the causal factors that underlie giving, and to design effective intervention programs that can help increase the likelihood and amount that people contribute to a cause. For charitable organizations, this book examines the efficacy of fundraising strategies commonly used by nonprofits and makes concrete recommendations about how to make capital campaigns more efficient and effective. Moreover, a number of novel factors that influence giving are identified and explored, opening the door to exciting new avenues in fundraising. For researchers, this book breaks novel theoretical ground in our understanding of how charitable decisions are made. While the chapters focus on applications to charity, the emotional, social, and cognitive mechanisms explored herein all have more general implications for the study of psychology and behavioral economics. This book highlights some of the most intriguing, surprising, and enlightening experimental studies on the topic of donation behavior, opening up exciting pathways to cross-cutting the divide between theory and practice. |
| data science for fundraising: Teaching Data Analytics Susan Vowels, Katherine Leaming Goldberg, 2019-06-17 The need for analytics skills is a source of the burgeoning growth in the number of analytics and decision science programs in higher education developed to feed the need for capable employees in this area. The very size and continuing growth of this need means that there is still space for new program development. Schools wishing to pursue business analytics programs intentionally assess the maturity level of their programs and take steps to close the gap. Teaching Data Analytics: Pedagogy and Program Design is a reference for faculty and administrators seeking direction about adding or enhancing analytics offerings at their institutions. It provides guidance by examining best practices from the perspectives of faculty and practitioners. By emphasizing the connection of data analytics to organizational success, it reviews the position of analytics and decision science programs in higher education, and to review the critical connection between this area of study and career opportunities. The book features: A variety of perspectives ranging from the scholarly theoretical to the practitioner applied An in-depth look into a wide breadth of skills from closely technology-focused to robustly soft human connection skills Resources for existing faculty to acquire and maintain additional analytics-relevant skills that can enrich their current course offerings. Acknowledging the dichotomy between data analytics and data science, this book emphasizes data analytics rather than data science, although the book does touch upon the data science realm. Starting with industry perspectives, the book covers the applied world of data analytics, covering necessary skills and applications, as well as developing compelling visualizations. It then dives into pedagogical and program design approaches in data analytics education and concludes with ideas for program design tactics. This reference is a launching point for discussions about how to connect industry’s need for skilled data analysts to higher education’s need to design a rigorous curriculum that promotes student critical thinking, communication, and ethical skills. It also provides insight into adding new elements to existing data analytics courses and for taking the next step in adding data analytics offerings, whether it be incorporating additional analytics assignments into existing courses, offering one course designed for undergraduates, or an integrated program designed for graduate students. |
| data science for fundraising: The Complete Guide to Fundraising Management Stanley Weinstein, Pamela Barden, 2017-02-28 The real-world guide to successfully funding your nonprofit program The Complete Guide to Fundraising Management is the comprehensive handbook for successful fundraising, with a practical focus that applies across the nonprofit sector. With a focus on planning, self-assessment, continual improvement, and high-payoff strategies, this book provides more than just ideas—it shows you the concrete, real-world actions that make it all happen, and gives you the tools you need to bring these concepts to life. This new fourth edition features the latest information about social media campaigning, internet fundraising, crowdfunding, and more. Timelines, checklists, and forms help you streamline management tasks to focus on effective development, and updated sample reports and budget information help you begin implementing these approaches quickly. The nonprofit world is becoming increasingly competitive in terms of funding, and fundraisers are being asked to perform miracles more than ever before. This book offers a time-tested framework for fundraising success, with step-by-step guidance through the entire process from prospect to program. Understand and apply the major principles and best practices of fundraising Manage information, resources, development, and volunteers Adopt new approaches to relationship-building and prospect identification Write grants and fundraising materials that make a rock-solid case for support There is never enough funding to go around. To survive and thrive, nonprofits must revitalize interest and generate more support. Gone are the days of door-knocking and bake sales; strategy is critical, and execution must be top-notch. The Complete Guide to Fundraising Management shows you the real-world strategies that get your programs funded. |
| data science for fundraising: Fundraising Michael J. Worth, 2015-07-21 Fundraising: Principles and Practice provides readers with a comprehensive introduction to fundraising. Taking a balanced perspective, bestselling author Michael J. Worth offers insights on the practical application of relevant theory. The text is designed to engage readers in thinking critically about issues in fundraising and philanthropy to prepare them for careers in the nonprofit sector. Worth explores donor motivations and fundraising techniques for annual giving programs, major gift programs, planned giving, and corporate and foundation giving and campaigns. Traditional methods, including direct mail and personal solicitations, are discussed as well as new tools and practices, including online fundraising, crowd-funding and social networks, analytics, and predictive modeling. Written specifically for nonprofit career-oriented individuals, this book helps readers become successful fundraisers. |
| data science for fundraising: Successful Fundraising for the Academic Library Kathryn Dilworth, Laura Sloop Henzl, 2016-10-07 Successful Fundraising for the Academic Library: Philanthropy in Higher Education covers fundraising, a task that is often grouped into a combination role that may include, for example, the university museum or performance venue, thus diluting the opportunity for successful fundraising. Because the traditional model for higher education fundraising entails the cultivation of alumni from specific departments and colleges, the library is traditionally left out, often becoming a low-performing development area with smaller appropriations for fundraising positions. Most higher education development professionals consider the library fundraising position a stepping stone into another position with higher pay and more potential for professional advancement down the road rather than as a focus for their career. However, for universities that invest in development professionals who know how to leverage the mission of libraries to the larger alumni and friend community, the results include innovative and successful approaches to messaging that resonates with donors. This book provides information that applies to all fundraising professionals and academic leaders looking to strengthen their programs with philanthropic support, even those beyond university libraries. - Makes the case for university libraries as a viable avenue for donor engagement that translates to all academic areas of higher education fundraising - Highlights the importance of collaborative relationships and fundraising strategies with academic leaders, donors, and fundraising staff - Outlines strategies that have resulted in fundraising success for academic and research libraries at universities of varying size and culture |
| data science for fundraising: The Life Science Executive's Fundraising Manifesto Dennis Ford, 2014-07-01 A primary objective for life science executives is raising capital. Very often, however, a lack of marketing and sales skills impedes their efforts. Focusing regionally, rather than globally, only compounds the challenge. The Life Science Executive's Fundraising Manifesto helps scientists understand the fundamental skills needed to brand and market their companies. It discusses how to use a consistent message to achieve compelling results from a fundraising campaign, and it teaches you how to aggregate a list of potential global investors that are a fit for your company's products and services. The book also explains how to efficiently and effectively reach out to potential investor targets, start a dialogue that fosters a relationship, and ultimately secure capital allocations. Raising capital is not a one-time event. It must be an ongoing part of your business strategy. This book reveals the expertise required to continually fundraise and bring your ideas to market. For more information about the book, please visit www.fundraisingmanifesto.com. |
| data science for fundraising: Modern Data Science with R Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton, 2021-03-31 From a review of the first edition: Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice. |
| data science for fundraising: Fundraising Principles for Faculty and Academic Leaders Aaron Conley, Genevieve G. Shaker, 2021-03-17 This book includes evidence-based insights and recommendations to help academicians excel in raising philanthropic support for their institutions and units. The book provides historical and contemporary perspectives on core concepts and data, research revealing donors’ giving motivations, engagement strategies and tactics for academic units, and guidance on management challenges including strategic plans, campaigns, and measuring performance. The authors include case studies in each section as examples of successful fundraising and volunteer-driven initiatives. The final section, contributed by Dean David D. Perlmutter, reinforces the book’s many practical and theoretical approaches to the fundamental responsibilities academic leaders face in raising philanthropic support. This book is grounded in the growing academic literature on philanthropy and written by scholars who were successful higher education fundraisers. |
| data science for fundraising: Donor Retention Roger M. Craver, 2014-08 There are eight main reasons why donors stop supporting organizations. Do you know them? You will after reading Retention Fundraising: The New Art and Science of Keeping Your Donors for Life. For three years, pioneering fundraiser Roger Craver immersed himself in a study of nonprofits in the U.S. and the U.K. His singular aim was to uncover why donors quit an organization and what can be done to make them stay. Some quick figures show why Craver's book on donor retention is timely: -If yours is a typical organization, you have a 60 to 70 percent chance of obtaining an additional gift from an existing donor. -You have a 20 to 40 percent chance of obtaining an additional gift from a recently lapsed donor. -But you have less than a 2 percent chance of obtaining a gift from a prospect. That bears repeating: The average organization has less than a 2 percent chance of securing a gift from a prospect. So one thing is glaringly obvious. The bulk of an organization's fundraising expenditures should be aimed at strengthening relationships with existing donors, not in acquiring new givers (though there's still a role for that, of course). Through painstaking research, Craver has singled out the exact ways an organization can deepen donor commitment. There are, he learned, seven key drivers that matter most to donors. These drivers - ranging from meaningful appreciation to opportunities for authentic involvement - have a direct cause-and- effect relationship. Move your donors from low to high commitment, and their giving will increase dramatically. Best of all, responding to what your donors want isn't costly, as Craver shows in real-life examples. There's gold in your current donors waiting to be mined. And in Retention Fundraising, Roger Craver has drawn a detailed map to those riches. |
| data science for fundraising: The Digital Fundraising Book Matt Howarth, Charlotte Taylor, Jordan Harling, 2016-03-31 This is the guide for charities and nonprofits to help you learn all you need to know about digital fundraising. It covers everything from the very basics, right up to the tricky stuff, like maximising conversion rates. A must-read for anyone wanting to develop their digital fundraising strategy. |
| data science for fundraising: Making the Ask Bernard Ross, Clare Segal, 2021-06-14 If you’re a fundraiser or social entrepreneur keen to secure large gift for any kind of social cause you need to be able to ask the right people for the right money in the right way. But how do you do that? In this ground-breaking book, global experts Bernard Ross and Clare Segal share their approach - used by major fundraising organisations from UNHCR in the Middle East to MSF in the US and from UK’s Oxford University to MEF Museum in Argentina – which has been used to secure gifts up to $110m in a single ask. Whether you’re an experienced fundraiser looking for new ideas, a newbie keen to get to the right approach fast, or a board member anxious to help out, you’ll find the answers you’re looking for inside. The book also has a special social bonus - every copy you buy will result in a donation to the WHO foundation to pay for a Covid 19 vaccine in a developing nation. “One reasonably useful book = one life-saving vaccine.” |
| data science for fundraising: Global Fundraising Penelope Cagney, Bernard Ross, 2013-02-25 A practical guide to the challenges and successes of global fundraising, written by an international team of highly respected philanthropy professionals and edited by two of the leading nonprofit thinkers, Global Fundraising is the first book to genuinely offer a global overview of philanthropy with an internationalist perspective. As the world becomes more interdependent, and economies struggle, global philanthropy continues to increase. More than that, nonprofits are taking up roles that have traditionally been filled by the government—including social welfare, healthcare, and human rights. Global Fundraising provides complete coverage of the implications of this growth for nonprofit culture and how it drives changes in fundraising practices. Organized into thematic chapters—a mixture of geographic and topical issues—it places North American philanthropy in a wider context It features a companion website with a variety of online tools and materials The book includes contributions by international leading experts Matt Ide, Mair Bosworth, Usha Menon, Anup Tiwari, Paula Guillet de Monthoux, Angela Cluff, Norma Galafassi, Mike Muchilwa, Tariq Cheema, Lu Bo and Nan Fang, Masataka Uo, Chris Carnie, Sean Triner, Andrea McManus, Marcelo Inniarra, Ashley Baldwin, Rebecca Mauger, YoungWoo Choi, R.F. Shangraw, Jr., Sudeshna Mukherjee, and Anca Zaharia. The book skillfully tracks how the world of fundraising is changing rapidly due to a number of factors including: continuing growth of great wealth; non-profit innovation emerging everywhere; growth of indigenous NGOs; increased professionalism in fundraising; and the value and role of new and social technologies. Written by a team of philanthropy leaders, Global Fundraising offers timely coverage of fundraising around the world. A must-have for INGO leaders and anyone, anywhere, interested in the future of philanthropy and effective fundraising practices. |
| data science for fundraising: Statistical and Machine-Learning Data Mining: Bruce Ratner, 2017-07-12 Interest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third edition of this bestseller, the author has completely revised, reorganized, and repositioned the original chapters and produced 13 new chapters of creative and useful machine-learning data mining techniques. In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. What is new in the Third Edition: The current chapters have been completely rewritten. The core content has been extended with strategies and methods for problems drawn from the top predictive analytics conference and statistical modeling workshops. Adds thirteen new chapters including coverage of data science and its rise, market share estimation, share of wallet modeling without survey data, latent market segmentation, statistical regression modeling that deals with incomplete data, decile analysis assessment in terms of the predictive power of the data, and a user-friendly version of text mining, not requiring an advanced background in natural language processing (NLP). Includes SAS subroutines which can be easily converted to other languages. As in the previous edition, this book offers detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. The author addresses each methodology and assigns its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with. |
| data science for fundraising: Donor-centered Fundraising Penelope Burk, 2018 Supported by dozens of studies over twenty years involving tens of thousands of donors, 'Donor-Centered Fundraising' paints a candid picture of why donors stop giving, and what it will take to preserve their ongoing loyalty in the future. In clear language and backed by statistical evidence, the book explores the pitfalls of the fundraising industry's traditional approaches to donor communication and recognition and clarifies what donors want but seldom get from the charities they support.--Publisher description. |
| data science for fundraising: Introduction to Data Science Rafael A. Irizarry, 2019-11-20 Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert. |
| data science for fundraising: Winning with Data Tomasz Tunguz, Frank Bien, 2016-06-20 Crest the data wave with a deep cultural shift Winning with Data explores the cultural changes big data brings to business, and shows you how to adapt your organization to leverage data to maximum effect. Authors Tomasz Tunguz and Frank Bien draw on extensive background in big data, business intelligence, and business strategy to provide a blueprint for companies looking to move head-on into the data wave. Instrumentation is discussed in detail, but the core of the change is in the culture—this book provides sound guidance on building the type of organizational culture that creates and leverages data daily, in every aspect of the business. Real-world examples illustrate these important concepts at work: you'll learn how data helped Warby-Parker disrupt a $13 billion monopolized market, how ThredUp uses data to process more than 20 thousand items of clothing every day, how Venmo leverages data to build better products, how HubSpot empowers their salespeople to be more productive, and more. From decision making and strategy to shipping and sales, this book shows you how data makes better business. Big data has taken on buzzword status, but there is little real guidance for companies seeking everyday business data solutions. This book takes a deeper look at big data in business, and shows you how to shift internal culture ahead of the curve. Understand the changes a data culture brings to companies Instrument your company for maximum benefit Utilize data to optimize every aspect of your business Improve decision making and transform business strategy Big data is becoming the number-one topic in business, yet no one is asking the right questions. Leveraging the full power of data requires more than good IT—organization-wide buy-in is essential for long-term success. Winning with Data is the expert guide to making data work for your business, and your needs. |
| data science for fundraising: Super Founders Ali Tamaseb, 2021-05-18 Super Founders uses a data-driven approach to understand what really differentiates billion-dollar startups from the rest—revealing that nearly everything we thought was true about them is false! Ali Tamaseb has spent thousands of hours manually amassing what may be the largest dataset ever collected on startups, comparing billion-dollar startups with those that failed to become one—30,000 data points on nearly every factor: number of competitors, market size, the founder’s age, his or her university’s ranking, quality of investors, fundraising time, and many, many more. And what he found looked far different than expected. Just to mention a few: Most unicorn founders had no industry experience; There's no disadvantage to being a solo founder or to being a non-technical CEO; Less than 15% went through any kind of accelerator program; Over half had strong competitors when starting--being first to market with an idea does not actually matter. You will also hear the stories of the early days of billion-dollar startups first-hand. The book includes exclusive interviews with the founders/investors of Zoom, Instacart, PayPal, Nest, Github, Flatiron Health, Kite Pharma, Facebook, Stripe, Airbnb, YouTube, LinkedIn, Lyft, DoorDash, Coinbase, and Square, venture capital investors like Elad Gil, Peter Thiel, Alfred Lin from Sequoia Capital and Keith Rabois of Founders Fund, as well as previously untold stories about the early days of ByteDance (TikTok), WhatsApp, Dropbox, Discord, DiDi, Flipkart, Instagram, Careem, Peloton, and SpaceX. Packed with counterintuitive insights and inside stories from people who have built massively successful companies, Super Founders is a paradigm-shifting and actionable guide for entrepreneurs, investors, and anyone interested in what makes a startup successful. |
| data science for fundraising: Data Mining for Business Analytics Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel, 2019-10-14 Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R |
| data science for fundraising: Analytics Stories Wayne L. Winston, 2020-09-02 Inform your own analyses by seeing how one of the best data analysts in the world approaches analytics problems Analytics Stories: How to Make Good Things Happen is a thoughtful, incisive, and entertaining exploration of the application of analytics to real-world problems and situations. Covering fields as diverse as sports, finance, politics, healthcare, and business, Analytics Stories bridges the gap between the oft inscrutable world of data analytics and the concrete problems it solves. Distinguished professor and author Wayne L. Winston answers questions like: Was Liverpool over Barcelona the greatest upset in sports history? Was Derek Jeter a great infielder What's wrong with the NFL QB rating? How did Madoff keep his fund going? Does a mutual fund’s past performance predict future performance? What caused the Crash of 2008? Can we predict where crimes are likely to occur? Is the lot of the American worker improving? How can analytics save the US Republic? The birth of evidence-based medicine: How did James Lind know citrus fruits cured scurvy? How can I objectively compare hospitals? How can we predict heart attacks in real time? How does a retail store know if you're pregnant? How can I use A/B testing to improve sales from my website? How can analytics help me write a hit song? Perfect for anyone with the word “analyst” in their job title, Analytics Stories illuminates the process of applying analytic principles to practical problems and highlights the potential pitfalls that await careless analysts. |
| data science for fundraising: Intuition, Trust, and Analytics Jay Liebowitz, Joanna Paliszkiewicz, Jerzy Gołuchowski, 2017-10-25 In order to make informed decisions, there are three important elements: intuition, trust, and analytics. Intuition is based on experiential learning and recent research has shown that those who rely on their “gut feelings” may do better than those who don’t. Analytics, however, are important in a data-driven environment to also inform decision making. The third element, trust, is critical for knowledge sharing to take place. These three elements—intuition, analytics, and trust—make a perfect combination for decision making. This book gathers leading researchers who explore the role of these three elements in the process of decision-making. |
| data science for fundraising: Fundraising for Impact in Libraries, Archives and Museums KATHRYN K. MATTHEW, 2021-12-31 Fundraising for Impact in Libraries, Archives and Museums provides practical advice that will help LAMs reassess how to leverage their organizational assets in ways that support communities and help to forge productive relationships with foundation, individual, corporate and government funders. Drawing on the insights gleaned from interviews with more than 100 international LAM practitioners, the book examines the common fundraising challenges that LAM institutions of all types and sizes face. During today's dynamic times, when many LAMs are seeking to remain relevant and viable, Matthew emphasizes how vital it is for them to demonstrate and communicate how they benefit their communities. The book presents five frameworks used in community development and philanthropy and illustrates how they can help an institution to assess and communicate its impact, focus its mission-related activities and effectively deploy proven fundraising strategies. Vignettes from the interviews are presented throughout, along with pointers, to illustrate actionable approaches that the reader can adapt as they seek contributed financial resources. The reader will explore various fundraising scenarios to help secure resources including appeals, special events, moves management, digital media, and corporate philanthropy. Fundraising for Impact in Libraries, Archives and Museums is essential reading for library, archive and museum practitioners and fundraisers working around the world. |
| data science for fundraising: Fundraising for Social Change Kim Klein, 2016-04-18 The bible of grassroots fundraising, updated with the latest tools and methods Fundraising for Social Change is the preeminent guide to securing funding, with a specific focus on progressive nonprofit organizations with budgets under $5 million. Used by nonprofits nationally and internationally, this book provides a soup-to-nuts prescription for building, maintaining, and expanding an individual donor program. Author Kim Klein is a recognized authority on all aspects of fundraising, and this book distills her decades of expertise into fundraising strategies that work. This updated seventh edition includes new information on the impact of generational change, using social media effectively, multi-channel fundraising, and more, including expanded discussion on retaining donors and on legacy giving. Widely considered the 'bible of grassroots fundraising,' this practically-grounded guide is an invaluable resource for anyone who has to raise money for important causes. A strong, sustainable fundraising strategy must possess certain characteristics. You need people who are willing to ask and realistic goals. You need to gather data and use it to improve results, and you need to translate your ideas in to language donors will understand. A robust individual donor program creates stable and long-term cash flow, and this book shows you how to structure your fundraising appropriately no matter how tight your initial budget. Develop and maintain a large base of individual donors Utilize strategies that pay off sooner rather than later Expand your reach and get your message out to the donor pool Translate traditional fundraising methods into strategies that work for social justice organizations with little or no front money Basing your fundraising strategy on the contributions of individual donors may feel like herding cats—but it's the best way for your organization to maintain maximum freedom to pursue the mission that matters. A robust, organized, planned approach can help you reach your goals sooner, and Fundraising for Social Change is the field guide for putting it all together to make big things happen. |
| data science for fundraising: Studying Those Who Study Us Diana Forsythe, 2001 Diana E. Forsythe was a leading anthropologist of science, technology, and work who pioneered the field of the anthropology of artificial intelligence. This volume collects her best-known essays, along with other major works that remained unpublished upon her death in 1997. It is also an exemplar of how reflexive ethnography should be done. |
| data science for fundraising: Joan Garry's Guide to Nonprofit Leadership Joan Garry, 2017-03-06 Nonprofit leadership is messy Nonprofits leaders are optimistic by nature. They believe with time, energy, smarts, strategy and sheer will, they can change the world. But as staff or board leader, you know nonprofits present unique challenges. Too many cooks, not enough money, an abundance of passion. It’s enough to make you feel overwhelmed and alone. The people you help need you to be successful. But there are so many obstacles: a micromanaging board that doesn’t understand its true role; insufficient fundraising and donors who make unreasonable demands; unclear and inconsistent messaging and marketing; a leader who’s a star in her sector but a difficult boss… And yet, many nonprofits do thrive. Joan Garry’s Guide to Nonprofit Leadership will show you how to do just that. Funny, honest, intensely actionable, and based on her decades of experience, this is the book Joan Garry wishes she had when she led GLAAD out of a financial crisis in 1997. Joan will teach you how to: Build a powerhouse board Create an impressive and sustainable fundraising program Become seen as a ‘workplace of choice’ Be a compelling public face of your nonprofit This book will renew your passion for your mission and organization, and help you make a bigger difference in the world. |
| data science for fundraising: You Are a Data Person Amelia Parnell, 2023-07-03 Internal and external pressure continues to mount for college professionals to provide evidence of successful activities, programs, and services, which means that, going forward, nearly every campus professional will need to approach their work with a data-informed perspective.But you find yourself thinking “I am not a data person”.Yes, you are. Or can be with the help of Amelia Parnell.You Are a Data Person provides context for the levels at which you are currently comfortable using data, helps you identify both the areas where you should strengthen your knowledge and where you can use this knowledge in your particular university role.For example, the rising cost to deliver high-quality programs and services to students has pushed many institutions to reallocate resources to find efficiencies. Also, more institutions are intentionally connecting classroom and cocurricular learning experiences which, in some instances, requires an increased gathering of evidence that students have acquired certain skills and competencies. In addition to programs, services, and pedagogy, professionals are constantly monitoring the rates at which students are entering, remaining enrolled in, and leaving the institution, as those movements impact the institution’s financial position.From teaching professors to student affairs personnel and beyond, Parnell offers tangible examples of how professionals can make data contributions at their current and future knowledge level, and will even inspire readers to take the initiative to engage in data projects.The book includes a set of self-assessment questions and a companion set of action steps and available resources to help readers accept their identity as a data person. It also includes an annotated list of at least 20 indicators that any higher education professional can examine without sophisticated data analyses. |
| data science for fundraising: Eventology Darren Diess, Michelle Gilmore, 2019-06-14 Hanging on to tradition is perfect for holidays and anniversaries, but fundraising today requires changing your strategy. The success of your fundraising event hinges upon being able to connect your audience to your organization's mission in a meaningful and memorable way. People donate to your organization because they are passionate about your cause and want to be part of something special; they want to make a difference. In Eventology, Darren Diess and Michelle Gilmore skillfully combine the art, science, and math of event fundraising to create a comprehensive resource guide to help you flawlessly execute a successful fundraising event, further your mission, and build long-term donor relationships that equate to sustainability for your cause. After reading Eventology, you will come away with the skills to develop an iron-clad event plan, build an interdisciplinary winning team, leverage technology to measure effectiveness, implement innovative funding techniques, expertly engage sponsors, and create a tailored event experience to build deep and lasting commitments from your donors. |
| data science for fundraising: The Smart Nonprofit Beth Kanter, Allison H. Fine, 2022-03-03 A pragmatic framework for nonprofit digital transformation that embraces the human-centered nature of your organization The Smart Nonprofit turns the page on an era of frantic busyness and scarcity mindsets to one in which nonprofit organizations have the time to think and plan — and even dream. The Smart Nonprofit offers a roadmap for the once-in-a-generation opportunity to remake work and accelerate positive social change. It comes from understanding how to use smart tech strategically, ethically and well. Smart tech does rote tasks like filling out expense reports and identifying prospective donors. However, it is also beginning to do very human things like screening applicants for jobs and social services, while paying forward historic biases. Beth Kanter and Allison Fine elegantly outline the ways smart nonprofits must stay human-centered and root out embedded bias in order to success at the compassionate and creative work that only humans can and should do. |
| data science for fundraising: The Zen of Fundraising Ken Burnett, 2011-01-13 If all that has ever been said and written about the art and science of fundraising could be distilled down to just what really matters—what fundraisers everywhere need to know—there would be only a small number of true gems deserving of the description, “nuggets of information.” Leading international fundraiser Ken Burnett, author of the classic Relationship Fundraising, has identified and defined 89 such nuggets which he presents here as The Zen of Fundraising, a fun read, one-of-a-kind look into what makes donors tick and–more importantly–what makes them give. |
| data science for fundraising: Formula for Fundraising Diana V. Hoyt, 2019-02-20 With Formula for Fundraising, Diana V. Hoyt walks nonprofits through the fundamentals of writing a fundraising plan and explains what to consider for each facet of the plan, making the fundraiser's task easier and the end result more successful. Full of solid, prescriptive advice, Formula for Fundraising contains real-world strategies that work. Designed to energize and empower fundraisers, you will learn how to: • Garner corporate and foundation support • Engage the board in fundraising • Cultivate major gift donations • Manage donor-advised funds • Acquire and retain donors • Secure tribute and corporate matching gifts • Understand generational giving You also will find valuable templates for: • Charitable Gift Acceptance Policies and Guidelines • Donor Recognition Policy • Case Statement • Donor Management Policies and Procedures • Fundraising Plan Formula for Fundraising helps any nonprofit reach its goal and support its mission, unlocking the organization's fundraising potential. |
| data science for fundraising: Introducing Data Science Davy Cielen, Arno Meysman, 2016-05-02 Summary Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Many companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering what you need to learn to begin a career as a data scientist can seem bewildering. This book is designed to help you get started. About the Book Introducing Data ScienceIntroducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You’ll explore data visualization, graph databases, the use of NoSQL, and the data science process. You’ll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you’ll have the solid foundation you need to start a career in data science. What’s Inside Handling large data Introduction to machine learning Using Python to work with data Writing data science algorithms About the Reader This book assumes you're comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required. About the Authors Davy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors. Table of Contents Data science in a big data world The data science process Machine learning Handling large data on a single computer First steps in big data Join the NoSQL movement The rise of graph databases Text mining and text analytics Data visualization to the end user |
| data science for fundraising: Asking Styles Brian Saber, 2018-07-04 This could very well become one of the most important books in our field. It is a breakthrough of a methodology that really works. It's the best antidote I've read on taking the fear out of asking. It will make you successful. If you already are, it will make you more so. (From the foreword by Jerold Panas.) The breakthrough concept of the Asking Styles makes it possible for anyone to become a more effective fundraiser. Your Asking Style is based on your personality and unique set of strengths when asking for gifts. If you've ever said to yourself I'm not a fundraiser or I don't fit the stereotype, embracing your Asking Style will change your entire mindset. Once you understand your strengths-and challenges-you'll be comfortable, confident and effective. You'll have a roadmap for dealing with donors. You'll know what to say, how to conduct meetings, and how to close gifts. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
