Data Practices

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Author :
Publisher : MIT Press
ISBN 13 : 1912685868
Total Pages : 257 pages
Book Rating : 4.9/5 (126 download)

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Book Synopsis Data Practices by : Evelyn Ruppert

Download or read book Data Practices written by Evelyn Ruppert and published by MIT Press. This book was released on 2021-11-02 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: How EU data practices establish and assign people to categories, and how this matters in enacting--"making up"--Europe as a population and people. What is "Europe" and who are "Europeans"? Data Practices approaches this contemporary political and theoretical question by treating it as a practical problem of counting. Only through the myriad data practices that make up methods such as censuses can EU member states know their national populations, and this in turn is utilized by the EU to understand the population of Europe. But this volume approaches data practices not simply as reflecting populations but as performative in two senses: they simultaneously enact--that is, "make up"--a European population and, by so doing--intentionally or otherwise--also contribute to making up a European people. The book develops a conception of data practices to analyze and interpret findings from collaborative ethnographic multisite fieldwork conducted by an interdisciplinary team of social science researchers as part of a five-year project, Peopling Europe: How Data Make a People. The book focuses on data practices that involve establishing and assigning people to categories and how this matters in enacting Europe as a population and people. Five core chapters explore key categories of people--usual residents, refugees, homeless people, migrants, and ethnic minorities--and how they come into being through specific data practices such as defining, estimating, recalibrating and inferring. Two additional chapters address two key subject positions that data practices produce and require: the data subject and the statistician subject.

Big Data

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Publisher : Simon and Schuster
ISBN 13 : 1638351104
Total Pages : 481 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Big Data by : James Warren

Download or read book Big Data written by James Warren and published by Simon and Schuster. This book was released on 2015-04-29 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth

Best Practices in Data Cleaning

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Author :
Publisher : SAGE
ISBN 13 : 1412988012
Total Pages : 297 pages
Book Rating : 4.4/5 (129 download)

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Book Synopsis Best Practices in Data Cleaning by : Jason W. Osborne

Download or read book Best Practices in Data Cleaning written by Jason W. Osborne and published by SAGE. This book was released on 2013 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many researchers jump straight from data collection to data analysis without realizing how analyses and hypothesis tests can go profoundly wrong without clean data. This book provides a clear, step-by-step process of examining and cleaning data in order to decrease error rates and increase both the power and replicability of results. Jason W. Osborne, author of Best Practices in Quantitative Methods (SAGE, 2008) provides easily-implemented suggestions that are research-based and will motivate change in practice by empirically demonstrating, for each topic, the benefits of following best practices and the potential consequences of not following these guidelines. If your goal is to do the best research you can do, draw conclusions that are most likely to be accurate representations of the population(s) you wish to speak about, and report results that are most likely to be replicated by other researchers, then this basic guidebook will be indispensible.

Data at Work

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Publisher : New Riders
ISBN 13 : 0134268784
Total Pages : 545 pages
Book Rating : 4.1/5 (342 download)

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Book Synopsis Data at Work by : Jorge Camões

Download or read book Data at Work written by Jorge Camões and published by New Riders. This book was released on 2016-04-08 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information visualization is a language. Like any language, it can be used for multiple purposes. A poem, a novel, and an essay all share the same language, but each one has its own set of rules. The same is true with information visualization: a product manager, statistician, and graphic designer each approach visualization from different perspectives. Data at Work was written with you, the spreadsheet user, in mind. This book will teach you how to think about and organize data in ways that directly relate to your work, using the skills you already have. In other words, you don’t need to be a graphic designer to create functional, elegant charts: this book will show you how. Although all of the examples in this book were created in Microsoft Excel, this is not a book about how to use Excel. Data at Work will help you to know which type of chart to use and how to format it, regardless of which spreadsheet application you use and whether or not you have any design experience. In this book, you’ll learn how to extract, clean, and transform data; sort data points to identify patterns and detect outliers; and understand how and when to use a variety of data visualizations including bar charts, slope charts, strip charts, scatter plots, bubble charts, boxplots, and more. Because this book is not a manual, it never specifies the steps required to make a chart, but the relevant charts will be available online for you to download, with brief explanations of how they were created.

R for Data Science

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491910364
Total Pages : 521 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis R for Data Science by : Hadley Wickham

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

The Open Handbook of Linguistic Data Management

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Publisher : MIT Press
ISBN 13 : 0262045265
Total Pages : 687 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Open Handbook of Linguistic Data Management by : Andrea L. Berez-Kroeker

Download or read book The Open Handbook of Linguistic Data Management written by Andrea L. Berez-Kroeker and published by MIT Press. This book was released on 2022-01-18 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to principles and methods for the management, archiving, sharing, and citing of linguistic research data, especially digital data. "Doing language science" depends on collecting, transcribing, annotating, analyzing, storing, and sharing linguistic research data. This volume offers a guide to linguistic data management, engaging with current trends toward the transformation of linguistics into a more data-driven and reproducible scientific endeavor. It offers both principles and methods, presenting the conceptual foundations of linguistic data management and a series of case studies, each of which demonstrates a concrete application of abstract principles in a current practice. In part 1, contributors bring together knowledge from information science, archiving, and data stewardship relevant to linguistic data management. Topics covered include implementation principles, archiving data, finding and using datasets, and the valuation of time and effort involved in data management. Part 2 presents snapshots of practices across various subfields, with each chapter presenting a unique data management project with generalizable guidance for researchers. The Open Handbook of Linguistic Data Management is an essential addition to the toolkit of every linguist, guiding researchers toward making their data FAIR: Findable, Accessible, Interoperable, and Reusable.

Data Management at Scale

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492054739
Total Pages : 404 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Data Management at Scale by : Piethein Strengholt

Download or read book Data Management at Scale written by Piethein Strengholt and published by "O'Reilly Media, Inc.". This book was released on 2020-07-29 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata

Discriminating Data

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Publisher : MIT Press
ISBN 13 : 0262046229
Total Pages : 341 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Discriminating Data by : Wendy Hui Kyong Chun

Download or read book Discriminating Data written by Wendy Hui Kyong Chun and published by MIT Press. This book was released on 2021-11-02 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: How big data and machine learning encode discrimination and create agitated clusters of comforting rage. In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is a goal—not an error—within big data and machine learning. These methods, she argues, encode segregation, eugenics, and identity politics through their default assumptions and conditions. Correlation, which grounds big data’s predictive potential, stems from twentieth-century eugenic attempts to “breed” a better future. Recommender systems foster angry clusters of sameness through homophily. Users are “trained” to become authentically predictable via a politics and technology of recognition. Machine learning and data analytics thus seek to disrupt the future by making disruption impossible. Chun, who has a background in systems design engineering as well as media studies and cultural theory, explains that although machine learning algorithms may not officially include race as a category, they embed whiteness as a default. Facial recognition technology, for example, relies on the faces of Hollywood celebrities and university undergraduates—groups not famous for their diversity. Homophily emerged as a concept to describe white U.S. resident attitudes to living in biracial yet segregated public housing. Predictive policing technology deploys models trained on studies of predominantly underserved neighborhoods. Trained on selected and often discriminatory or dirty data, these algorithms are only validated if they mirror this data. How can we release ourselves from the vice-like grip of discriminatory data? Chun calls for alternative algorithms, defaults, and interdisciplinary coalitions in order to desegregate networks and foster a more democratic big data.

Development Research in Practice

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Author :
Publisher : World Bank Publications
ISBN 13 : 1464816956
Total Pages : 388 pages
Book Rating : 4.4/5 (648 download)

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Book Synopsis Development Research in Practice by : Kristoffer Bjärkefur

Download or read book Development Research in Practice written by Kristoffer Bjärkefur and published by World Bank Publications. This book was released on 2021-07-16 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University

Storytelling with Data

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Publisher : John Wiley & Sons
ISBN 13 : 1119002265
Total Pages : 288 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Storytelling with Data by : Cole Nussbaumer Knaflic

Download or read book Storytelling with Data written by Cole Nussbaumer Knaflic and published by John Wiley & Sons. This book was released on 2015-10-09 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!

Sharing Clinical Trial Data

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Publisher : National Academies Press
ISBN 13 : 0309316324
Total Pages : 304 pages
Book Rating : 4.3/5 (93 download)

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Book Synopsis Sharing Clinical Trial Data by : Institute of Medicine

Download or read book Sharing Clinical Trial Data written by Institute of Medicine and published by National Academies Press. This book was released on 2015-04-20 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research--from funders, to researchers, to journals, to physicians, and ultimately, to patients.

Information Governance Principles and Practices for a Big Data Landscape

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Author :
Publisher : IBM Redbooks
ISBN 13 : 0738439592
Total Pages : 280 pages
Book Rating : 4.7/5 (384 download)

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Book Synopsis Information Governance Principles and Practices for a Big Data Landscape by : Chuck Ballard

Download or read book Information Governance Principles and Practices for a Big Data Landscape written by Chuck Ballard and published by IBM Redbooks. This book was released on 2014-03-31 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IBM® Redbooks® publication describes how the IBM Big Data Platform provides the integrated capabilities that are required for the adoption of Information Governance in the big data landscape. As organizations embark on new use cases, such as Big Data Exploration, an enhanced 360 view of customers, or Data Warehouse modernization, and absorb ever growing volumes and variety of data with accelerating velocity, the principles and practices of Information Governance become ever more critical to ensure trust in data and help organizations overcome the inherent risks and achieve the wanted value. The introduction of big data changes the information landscape. Data arrives faster than humans can react to it, and issues can quickly escalate into significant events. The variety of data now poses new privacy and security risks. The high volume of information in all places makes it harder to find where these issues, risks, and even useful information to drive new value and revenue are. Information Governance provides an organization with a framework that can align their wanted outcomes with their strategic management principles, the people who can implement those principles, and the architecture and platform that are needed to support the big data use cases. The IBM Big Data Platform, coupled with a framework for Information Governance, provides an approach to build, manage, and gain significant value from the big data landscape.

Developing Data Migrations and Integrations with Salesforce

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Author :
Publisher : Apress
ISBN 13 : 1484242092
Total Pages : 359 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Developing Data Migrations and Integrations with Salesforce by : David Masri

Download or read book Developing Data Migrations and Integrations with Salesforce written by David Masri and published by Apress. This book was released on 2018-12-18 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Migrate your data to Salesforce and build low-maintenance and high-performing data integrations to get the most out of Salesforce and make it a "go-to" place for all your organization's customer information. When companies choose to roll out Salesforce, users expect it to be the place to find any and all Information related to a customer—the coveted Client 360° view. On the day you go live, users expect to see all their accounts, contacts, and historical data in the system. They also expect that data entered in other systems will be exposed in Salesforce automatically and in a timely manner. This book shows you how to migrate all your legacy data to Salesforce and then design integrations to your organization's mission-critical systems. As the Salesforce platform grows more powerful, it also grows in complexity. Whether you are migrating data to Salesforce, or integrating with Salesforce, it is important to understand how these complexities need to be reflected in your design. Developing Data Migrations and Integrations with Salesforce covers everything you need to know to migrate your data to Salesforce the right way, and how to design low-maintenance, high-performing data integrations with Salesforce. This book is written by a practicing Salesforce integration architect with dozens of Salesforce projects under his belt. The patterns and practices covered in this book are the results of the lessons learned during those projects. What You’ll Learn Know how Salesforce’s data engine is architected and why Use the Salesforce Data APIs to load and extract data Plan and execute your data migration to Salesforce Design low-maintenance, high-performing data integrations with Salesforce Understand common data integration patterns and the pros and cons of each Know real-time integration options for Salesforce Be aware of common pitfalls Build reusable transformation code covering commonly needed Salesforce transformation patterns Who This Book Is For Those tasked with migrating data to Salesforce or building ongoing data integrations with Salesforce, regardless of the ETL tool or middleware chosen; project sponsors or managers nervous about data tracks putting their projects at risk; aspiring Salesforce integration and/or migration specialists; Salesforce developers or architects looking to expand their skills and take on new challenges

The Rise of Big Data Policing

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Publisher : NYU Press
ISBN 13 : 147986997X
Total Pages : 267 pages
Book Rating : 4.4/5 (798 download)

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Book Synopsis The Rise of Big Data Policing by : Andrew Guthrie Ferguson

Download or read book The Rise of Big Data Policing written by Andrew Guthrie Ferguson and published by NYU Press. This book was released on 2019-11-15 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: Winner, 2018 Law & Legal Studies PROSE Award The consequences of big data and algorithm-driven policing and its impact on law enforcement In a high-tech command center in downtown Los Angeles, a digital map lights up with 911 calls, television monitors track breaking news stories, surveillance cameras sweep the streets, and rows of networked computers link analysts and police officers to a wealth of law enforcement intelligence. This is just a glimpse into a future where software predicts future crimes, algorithms generate virtual “most-wanted” lists, and databanks collect personal and biometric information. The Rise of Big Data Policing introduces the cutting-edge technology that is changing how the police do their jobs and shows why it is more important than ever that citizens understand the far-reaching consequences of big data surveillance as a law enforcement tool. Andrew Guthrie Ferguson reveals how these new technologies —viewed as race-neutral and objective—have been eagerly adopted by police departments hoping to distance themselves from claims of racial bias and unconstitutional practices. After a series of high-profile police shootings and federal investigations into systemic police misconduct, and in an era of law enforcement budget cutbacks, data-driven policing has been billed as a way to “turn the page” on racial bias. But behind the data are real people, and difficult questions remain about racial discrimination and the potential to distort constitutional protections. In this first book on big data policing, Ferguson offers an examination of how new technologies will alter the who, where, when and how we police. These new technologies also offer data-driven methods to improve police accountability and to remedy the underlying socio-economic risk factors that encourage crime. The Rise of Big Data Policing is a must read for anyone concerned with how technology will revolutionize law enforcement and its potential threat to the security, privacy, and constitutional rights of citizens. Read an excerpt and interview with Andrew Guthrie Ferguson in The Economist.

Attitudes towards big data practices and the institutional framework of privacy and data protection - A population survey

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Author :
Publisher : KIT Scientific Publishing
ISBN 13 : 3731508591
Total Pages : 88 pages
Book Rating : 4.7/5 (315 download)

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Book Synopsis Attitudes towards big data practices and the institutional framework of privacy and data protection - A population survey by : Orwat, Carsten

Download or read book Attitudes towards big data practices and the institutional framework of privacy and data protection - A population survey written by Orwat, Carsten and published by KIT Scientific Publishing. This book was released on 2019-01-14 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Forecasting: principles and practice

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Author :
Publisher : OTexts
ISBN 13 : 0987507117
Total Pages : 380 pages
Book Rating : 4.9/5 (875 download)

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Book Synopsis Forecasting: principles and practice by : Rob J Hyndman

Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

Impact Evaluation in Practice, Second Edition

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Author :
Publisher : World Bank Publications
ISBN 13 : 1464807809
Total Pages : 364 pages
Book Rating : 4.4/5 (648 download)

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Book Synopsis Impact Evaluation in Practice, Second Edition by : Paul J. Gertler

Download or read book Impact Evaluation in Practice, Second Edition written by Paul J. Gertler and published by World Bank Publications. This book was released on 2016-09-12 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of the Impact Evaluation in Practice handbook is a comprehensive and accessible introduction to impact evaluation for policy makers and development practitioners. First published in 2011, it has been used widely across the development and academic communities. The book incorporates real-world examples to present practical guidelines for designing and implementing impact evaluations. Readers will gain an understanding of impact evaluations and the best ways to use them to design evidence-based policies and programs. The updated version covers the newest techniques for evaluating programs and includes state-of-the-art implementation advice, as well as an expanded set of examples and case studies that draw on recent development challenges. It also includes new material on research ethics and partnerships to conduct impact evaluation. The handbook is divided into four sections: Part One discusses what to evaluate and why; Part Two presents the main impact evaluation methods; Part Three addresses how to manage impact evaluations; Part Four reviews impact evaluation sampling and data collection. Case studies illustrate different applications of impact evaluations. The book links to complementary instructional material available online, including an applied case as well as questions and answers. The updated second edition will be a valuable resource for the international development community, universities, and policy makers looking to build better evidence around what works in development.