Cover -- Half-title -- Title -- Copyright -- Contents -- Introduction -- PART I: ENGAGING THE DATA -- 1 Measuring Political and Policy Preferences Using Item Response Scaling -- 2 Causal Inference with Observational Data -- 3 Causal Inference with Experimental Data -- PART II: EMERGING DATA SOURCES AND TECHNIQUES -- 4 Descriptive Network Analysis: Interest Group Lobbying Dynamics Around Immigration Policy -- 5 Learning from Place in the Era of Geolocation -- 6 Text Analysis: Estimating Policy Preferences from Written and Spoken Words -- 7 Machine Learning and Governance -- PART III: IMPLICATIONS FOR GOVERNANCE -- 8 Governing a Data-Driven Society -- 9 Big Data and Privacy -- 10 Reflections on Analytics: Knowledge and Power -- List of Contributors -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- V -- W -- Y
Public Policy Analytics: Code & Context for Data Science in Government teaches readers how to address complex public policy problems with data and analytics using reproducible methods in R. Each of the eight chapters provides a detailed case study, showing readers: how to develop exploratory indicators; understand ‘spatial process’ and develop spatial analytics; how to develop ‘useful’ predictive analytics; how to convey these outputs to non-technical decision-makers through the medium of data visualization; and why, ultimately, data science and ‘Planning’ are one and the same. A graduate-level introduction to data science, this book will appeal to researchers and data scientists at the intersection of data analytics and public policy, as well as readers who wish to understand how algorithms will affect the future of government.
The first available textbook on the rapidly growing and increasingly important field of government analytics This first textbook on the increasingly important field of government analytics provides invaluable knowledge and training for students of government in the synthesis, interpretation, and communication of big data, which is now an integral part of governance and policy making. Integrating all the major components of this rapidly growing field, this invaluable text explores the intricate relationship of data analytics to governance while providing innovative strategies for the retrieval and management of information.
Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.
Analytics can make government work better—this book shows you how A Practical Guide to Analytics for Governments provides demonstrations of real-world analytics applications for legislators, policy-makers, and support staff at the federal, state, and local levels. Big data and analytics are transforming industries across the board, and government can reap many of those same benefits by applying analytics to processes and programs already in place. From healthcare delivery and child well-being, to crime and program fraud, analytics can—in fact, already does—transform the way government works. This book shows you how analytics can be implemented in your own milieu: What is the downstream impact of new legislation? How can we make programs more efficient? Is it possible to predict policy outcomes without analytics? How do I get started building analytics into my government organization? The answers are all here, with accessible explanations and useful advice from an expert in the field. Analytics allows you to mine your data to create a holistic picture of your constituents; this model helps you tailor programs, fine-tune legislation, and serve the populace more effectively. This book walks you through analytics as applied to government, and shows you how to reap Big data's benefits at whatever level necessary. Learn how analytics is already transforming government service delivery Delve into the digital healthcare revolution Use analytics to improve education, juvenile justice, and other child-focused areas Apply analytics to transportation, criminal justice, fraud, and much more Legislators and policy makers have plenty of great ideas—but how do they put those ideas into play? Analytics can play a crucial role in getting the job done well. A Practical Guide to Analytics for Governments provides advice, perspective, and real-world guidance for public servants everywhere.
Project governance, investment governance, and risk governance precepts are woven together in Self-Service Data Analytics and Governance for Managers, equipping managers to structure the inevitable chaos that can result as end-users take matters into their own hands Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving environment of digital transformation in the finance, accounting, and operations world, where entire functions spend their days processing in spreadsheets. With the decentralization of application development as users perform their own analysis on data sets and automate spreadsheet processing without the involvement of IT, governance must be revisited to maintain process control in the new environment. In this book, emergent technologies that have given rise to data analytics and which form the evolving backdrop for digital transformation are introduced and explained, and prominent data analytics tools and capabilities will be demonstrated based on real world scenarios. The authors will provide a much-needed process discovery methodology describing how to survey the processing landscape to identify opportunities to deploy these capabilities. Perhaps most importantly, the authors will digest the mature existing data governance, IT governance, and model governance frameworks, but demonstrate that they do not comprehensively cover the full suite of data analytics builds, leaving a considerable governance gap. This book is meant to fill the gap and provide the reader with a fit-for-purpose and actionable governance framework to protect the value created by analytics deployment at scale. Project governance, investment governance, and risk governance precepts will be woven together to equip managers to structure the inevitable chaos that can result as end-users take matters into their own hands.
What kind of policy analysis is required now that governments increasingly encounter the limits of governing? Exploring the new contexts of politics and policy making, this book presents an original analysis of the relationship between state and society, and new possibilities for collective learning and conflict resolution. The key insight of the book is that democratic governance calls for a new deliberatively-oriented policy analysis. Traditionally policy analysis has been state-centered, based on the assumption that central government is self-evidently the locus of governing. Drawing on detailed empirical examples, the book examines the influence of developments such as increasing ethnic and cultural diversity, the complexity of socio-technical systems, and the impact of transnational arrangements on national policy making. This contextual approach indicates the need to rethink the relationship between social theory, policy analysis, and politics. The book is essential reading for all those involved in the study of public policy.
Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program. - Incorporates industry changes, lessons learned and new approaches - Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations - Includes new case studies which detail real-world situations - Explores all of the capabilities an organization must adopt to become data driven - Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional - Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities - Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy - Provides up to 75% brand-new content compared to the first edition
Data-governance programs focus on authority and accountability for the management of data as a valued organizational asset. Data Governance should not be about command-and-control, yet at times could become invasive or threatening to the work, people and culture of an organization. Non-Invasive Data Governance™ focuses on formalizing existing accountability for the management of data and improving formal communications, protection, and quality efforts through effective stewarding of data resources. Non-Invasive Data Governance will provide you with a complete set of tools to help you deliver a successful data governance program. Learn how: • Steward responsibilities can be identified and recognized, formalized, and engaged according to their existing responsibility rather than being assigned or handed to people as more work. • Governance of information can be applied to existing policies, standard operating procedures, practices, and methodologies, rather than being introduced or emphasized as new processes or methods. • Governance of information can support all data integration, risk management, business intelligence and master data management activities rather than imposing inconsistent rigor to these initiatives. • A practical and non-threatening approach can be applied to governing information and promoting stewardship of data as a cross-organization asset. • Best practices and key concepts of this non-threatening approach can be communicated effectively to leverage strengths and address opportunities to improve.
