Fundraising Analytics

Fundraising Analytics PDF Author: Joshua M. Birkholz
Publisher: Wiley
ISBN: 9780470165577
Category : Business & Economics
Languages : en
Pages : 240

Get Book

Book Description
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.

Intuition, Trust, and Analytics

Intuition, Trust, and Analytics PDF Author: Jay Liebowitz
Publisher: CRC Press
ISBN: 135176439X
Category : Computers
Languages : en
Pages : 266

Get Book

Book Description
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.

R for Political Data Science

R for Political Data Science PDF Author: Francisco Urdinez
Publisher: CRC Press
ISBN: 1000204472
Category : Political Science
Languages : en
Pages : 440

Get Book

Book Description
R for Political Data Science: A Practical Guide is a handbook for political scientists new to R who want to learn the most useful and common ways to interpret and analyze political data. It was written by political scientists, thinking about the many real-world problems faced in their work. The book has 16 chapters and is organized in three sections. The first, on the use of R, is for those users who are learning R or are migrating from another software. The second section, on econometric models, covers OLS, binary and survival models, panel data, and causal inference. The third section is a data science toolbox of some the most useful tools in the discipline: data imputation, fuzzy merge of large datasets, web mining, quantitative text analysis, network analysis, mapping, spatial cluster analysis, and principal component analysis. Key features: Each chapter has the most up-to-date and simple option available for each task, assuming minimal prerequisites and no previous experience in R Makes extensive use of the Tidyverse, the group of packages that has revolutionized the use of R Provides a step-by-step guide that you can replicate using your own data Includes exercises in every chapter for course use or self-study Focuses on practical-based approaches to statistical inference rather than mathematical formulae Supplemented by an R package, including all data As the title suggests, this book is highly applied in nature, and is designed as a toolbox for the reader. It can be used in methods and data science courses, at both the undergraduate and graduate levels. It will be equally useful for a university student pursuing a PhD, political consultants, or a public official, all of whom need to transform their datasets into substantive and easily interpretable conclusions.

Data Science for Fundraising

Data Science for Fundraising PDF Author: Ashutosh R Nandeshwar
Publisher: Data Insight Partners LLC
ISBN: 9780692057841
Category : Business & Economics
Languages : en
Pages : 568

Get Book

Book Description
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.

Teaching Data Analytics

Teaching Data Analytics PDF Author: Susan A Vowels
Publisher: CRC Press
ISBN: 1351721445
Category : Computers
Languages : en
Pages : 202

Get Book

Book Description
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.

Introducing Data Science

Introducing Data Science PDF Author: Davy Cielen
Publisher: Simon and Schuster
ISBN: 1638352496
Category : Computers
Languages : en
Pages : 320

Get Book

Book Description
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

Fundraising Analytics

Fundraising Analytics PDF Author: Joshua M. Birkholz
Publisher: John Wiley & Sons
ISBN: 111978235X
Category : Business & Economics
Languages : en
Pages : 243

Get Book

Book Description
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.

How to Lead in Data Science

How to Lead in Data Science PDF Author: Jike Chong
Publisher: Simon and Schuster
ISBN: 1617298891
Category : Computers
Languages : en
Pages : 512

Get Book

Book Description
A field guide for the unique challenges of data science leadership, filled with transformative insights, personal experiences, and industry examples. In How To Lead in Data Science you will learn: Best practices for leading projects while balancing complex trade-offs Specifying, prioritizing, and planning projects from vague requirements Navigating structural challenges in your organization Working through project failures with positivity and tenacity Growing your team with coaching, mentoring, and advising Crafting technology roadmaps and championing successful projects Driving diversity, inclusion, and belonging within teams Architecting a long-term business strategy and data roadmap as an executive Delivering a data-driven culture and structuring productive data science organizations How to Lead in Data Science is full of techniques for leading data science at every seniority level—from heading up a single project to overseeing a whole company's data strategy. Authors Jike Chong and Yue Cathy Chang share hard-won advice that they've developed building data teams for LinkedIn, Acorns, Yiren Digital, large asset-management firms, Fortune 50 companies, and more. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away. Carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and highlight development areas. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive as a data science leader at all levels, from team member to the C-suite. About the book How to Lead in Data Science shares unique leadership techniques from high-performance data teams. It’s filled with best practices for balancing project trade-offs and producing exceptional results, even when beginning with vague requirements or unclear expectations. You’ll find a clearly presented modern leadership framework based on current case studies, with insights reaching all the way to Aristotle and Confucius. As you read, you’ll build practical skills to grow and improve your team, your company’s data culture, and yourself. What's inside How to coach and mentor team members Navigate an organization’s structural challenges Secure commitments from other teams and partners Stay current with the technology landscape Advance your career About the reader For data science practitioners at all levels. About the author Dr. Jike Chong and Yue Cathy Chang build, lead, and grow high-performing data teams across industries in public and private companies, such as Acorns, LinkedIn, large asset-management firms, and Fortune 50 companies. Table of Contents 1 What makes a successful data scientist? PART 1 THE TECH LEAD: CULTIVATING LEADERSHIP 2 Capabilities for leading projects 3 Virtues for leading projects PART 2 THE MANAGER: NURTURING A TEAM 4 Capabilities for leading people 5 Virtues for leading people PART 3 THE DIRECTOR: GOVERNING A FUNCTION 6 Capabilities for leading a function 7 Virtues for leading a function PART 4 THE EXECUTIVE: INSPIRING AN INDUSTRY 8 Capabilities for leading a company 9 Virtues for leading a company PART 5 THE LOOP AND THE FUTURE 10 Landscape, organization, opportunity, and practice 11 Leading in data science and a future outlook

The Routledge Companion to Nonprofit Management

The Routledge Companion to Nonprofit Management PDF Author: Helmut K. Anheier
Publisher: Routledge
ISBN: 1351721054
Category : Business & Economics
Languages : en
Pages : 546

Get Book

Book Description
Over the past three decades or so, the nonprofit, voluntary, or third sector has undergone a major transformation from a small cottage industry to a major economic force in virtually every part of the developed world as well as elsewhere around the globe. Nonprofit organizations are now major providers of public services working in close cooperation with governments at all levels and increasingly find themselves in competition with commercial firms across various social marketplaces. This transformation has come with ever-increasing demands for enhancing the organizational capacities and professionalizing the management of nonprofit institutions. The Routledge Companion to Nonprofit Management is the first internationally focused effort to capture the full breadth of current nonprofit management research and knowledge that has arisen in response to these developments. With newly commissioned contributions from an international set of scholars at the forefront of nonprofit management research, this volume provides a thorough overview of the most current management thinking in this field. It contextualizes nonprofit management globally, provides an extensive introduction to key management functions, core revenue sources and the emerging social enterprise space, and raises a number of emerging topics and issues that will shape nonprofit management in future decades. As graduate programs continue to evolve to serve the training needs in the field, The Routledge Companion to Nonprofit Management is an essential reference and resource for graduate students, researchers, and practitioners interested in a deeper understanding of the operation of the nonprofit sector.

Sport Public Relations

Sport Public Relations PDF Author: G. Clayton Stoldt
Publisher: Human Kinetics Publishers
ISBN: 1492589381
Category : Communication in organizations
Languages : en
Pages : 304

Get Book

Book Description
"The text provides students and professionals with an understanding of all aspects of sport public relations, framing its discussion in terms of a managerial and proactive approach to PR"--

Fundraising Analytics

Fundraising Analytics PDF Author: Joshua M. Birkholz
Publisher: Wiley
ISBN: 9780470165577
Category : Business & Economics
Languages : en
Pages : 240

View

Book Description
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.

Intuition, Trust, and Analytics

Intuition, Trust, and Analytics PDF Author: Jay Liebowitz
Publisher: CRC Press
ISBN: 135176439X
Category : Computers
Languages : en
Pages : 266

View

Book Description
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.

R for Political Data Science

R for Political Data Science PDF Author: Francisco Urdinez
Publisher: CRC Press
ISBN: 1000204472
Category : Political Science
Languages : en
Pages : 440

View

Book Description
R for Political Data Science: A Practical Guide is a handbook for political scientists new to R who want to learn the most useful and common ways to interpret and analyze political data. It was written by political scientists, thinking about the many real-world problems faced in their work. The book has 16 chapters and is organized in three sections. The first, on the use of R, is for those users who are learning R or are migrating from another software. The second section, on econometric models, covers OLS, binary and survival models, panel data, and causal inference. The third section is a data science toolbox of some the most useful tools in the discipline: data imputation, fuzzy merge of large datasets, web mining, quantitative text analysis, network analysis, mapping, spatial cluster analysis, and principal component analysis. Key features: Each chapter has the most up-to-date and simple option available for each task, assuming minimal prerequisites and no previous experience in R Makes extensive use of the Tidyverse, the group of packages that has revolutionized the use of R Provides a step-by-step guide that you can replicate using your own data Includes exercises in every chapter for course use or self-study Focuses on practical-based approaches to statistical inference rather than mathematical formulae Supplemented by an R package, including all data As the title suggests, this book is highly applied in nature, and is designed as a toolbox for the reader. It can be used in methods and data science courses, at both the undergraduate and graduate levels. It will be equally useful for a university student pursuing a PhD, political consultants, or a public official, all of whom need to transform their datasets into substantive and easily interpretable conclusions.

Data Science for Fundraising

Data Science for Fundraising PDF Author: Ashutosh R Nandeshwar
Publisher: Data Insight Partners LLC
ISBN: 9780692057841
Category : Business & Economics
Languages : en
Pages : 568

View

Book Description
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.

Teaching Data Analytics

Teaching Data Analytics PDF Author: Susan A Vowels
Publisher: CRC Press
ISBN: 1351721445
Category : Computers
Languages : en
Pages : 202

View

Book Description
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.

Introducing Data Science

Introducing Data Science PDF Author: Davy Cielen
Publisher: Simon and Schuster
ISBN: 1638352496
Category : Computers
Languages : en
Pages : 320

View

Book Description
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

Fundraising Analytics

Fundraising Analytics PDF Author: Joshua M. Birkholz
Publisher: John Wiley & Sons
ISBN: 111978235X
Category : Business & Economics
Languages : en
Pages : 243

View

Book Description
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.

How to Lead in Data Science

How to Lead in Data Science PDF Author: Jike Chong
Publisher: Simon and Schuster
ISBN: 1617298891
Category : Computers
Languages : en
Pages : 512

View

Book Description
A field guide for the unique challenges of data science leadership, filled with transformative insights, personal experiences, and industry examples. In How To Lead in Data Science you will learn: Best practices for leading projects while balancing complex trade-offs Specifying, prioritizing, and planning projects from vague requirements Navigating structural challenges in your organization Working through project failures with positivity and tenacity Growing your team with coaching, mentoring, and advising Crafting technology roadmaps and championing successful projects Driving diversity, inclusion, and belonging within teams Architecting a long-term business strategy and data roadmap as an executive Delivering a data-driven culture and structuring productive data science organizations How to Lead in Data Science is full of techniques for leading data science at every seniority level—from heading up a single project to overseeing a whole company's data strategy. Authors Jike Chong and Yue Cathy Chang share hard-won advice that they've developed building data teams for LinkedIn, Acorns, Yiren Digital, large asset-management firms, Fortune 50 companies, and more. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away. Carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and highlight development areas. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive as a data science leader at all levels, from team member to the C-suite. About the book How to Lead in Data Science shares unique leadership techniques from high-performance data teams. It’s filled with best practices for balancing project trade-offs and producing exceptional results, even when beginning with vague requirements or unclear expectations. You’ll find a clearly presented modern leadership framework based on current case studies, with insights reaching all the way to Aristotle and Confucius. As you read, you’ll build practical skills to grow and improve your team, your company’s data culture, and yourself. What's inside How to coach and mentor team members Navigate an organization’s structural challenges Secure commitments from other teams and partners Stay current with the technology landscape Advance your career About the reader For data science practitioners at all levels. About the author Dr. Jike Chong and Yue Cathy Chang build, lead, and grow high-performing data teams across industries in public and private companies, such as Acorns, LinkedIn, large asset-management firms, and Fortune 50 companies. Table of Contents 1 What makes a successful data scientist? PART 1 THE TECH LEAD: CULTIVATING LEADERSHIP 2 Capabilities for leading projects 3 Virtues for leading projects PART 2 THE MANAGER: NURTURING A TEAM 4 Capabilities for leading people 5 Virtues for leading people PART 3 THE DIRECTOR: GOVERNING A FUNCTION 6 Capabilities for leading a function 7 Virtues for leading a function PART 4 THE EXECUTIVE: INSPIRING AN INDUSTRY 8 Capabilities for leading a company 9 Virtues for leading a company PART 5 THE LOOP AND THE FUTURE 10 Landscape, organization, opportunity, and practice 11 Leading in data science and a future outlook

The Routledge Companion to Nonprofit Management

The Routledge Companion to Nonprofit Management PDF Author: Helmut K. Anheier
Publisher: Routledge
ISBN: 1351721054
Category : Business & Economics
Languages : en
Pages : 546

View

Book Description
Over the past three decades or so, the nonprofit, voluntary, or third sector has undergone a major transformation from a small cottage industry to a major economic force in virtually every part of the developed world as well as elsewhere around the globe. Nonprofit organizations are now major providers of public services working in close cooperation with governments at all levels and increasingly find themselves in competition with commercial firms across various social marketplaces. This transformation has come with ever-increasing demands for enhancing the organizational capacities and professionalizing the management of nonprofit institutions. The Routledge Companion to Nonprofit Management is the first internationally focused effort to capture the full breadth of current nonprofit management research and knowledge that has arisen in response to these developments. With newly commissioned contributions from an international set of scholars at the forefront of nonprofit management research, this volume provides a thorough overview of the most current management thinking in this field. It contextualizes nonprofit management globally, provides an extensive introduction to key management functions, core revenue sources and the emerging social enterprise space, and raises a number of emerging topics and issues that will shape nonprofit management in future decades. As graduate programs continue to evolve to serve the training needs in the field, The Routledge Companion to Nonprofit Management is an essential reference and resource for graduate students, researchers, and practitioners interested in a deeper understanding of the operation of the nonprofit sector.

Sport Public Relations

Sport Public Relations PDF Author: G. Clayton Stoldt
Publisher: Human Kinetics Publishers
ISBN: 1492589381
Category : Communication in organizations
Languages : en
Pages : 304

View

Book Description
"The text provides students and professionals with an understanding of all aspects of sport public relations, framing its discussion in terms of a managerial and proactive approach to PR"--