Data For All
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| Author | : Yanni Alexander Loukissas |
| Publisher | : MIT Press |
| Total Pages | : 267 |
| Release | : 2019-04-30 |
| Genre | : Computers |
| ISBN | : 0262039664 |
How to analyze data settings rather than data sets, acknowledging the meaning-making power of the local. In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local, we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. The term data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States—Harvard's Arnold Arboretum, the Digital Public Library of America, UCLA's Television News Archive, and the real estate marketplace Zillow—Loukissas shows us how to analyze data settings rather than data sets. Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogeneous sources; data and algorithms are inextricably entangled; interfaces recontextualize data; and data are indexes to local knowledge. He then provides a set of practical guidelines to follow. To make his argument, Loukissas employs a combination of qualitative research on data cultures and exploratory data visualizations. Rebutting the “myth of digital universalism,” Loukissas reminds us of the meaning-making power of the local.
| Author | : Nancy Love |
| Publisher | : Corwin Press |
| Total Pages | : 193 |
| Release | : 2009 |
| Genre | : Education |
| ISBN | : 1412960851 |
Collaborative inquiry + effective use of data = significant leaps in learning and achievement! This resource combines a powerful collaborative inquiry process, reflective dialogue, and rigorous use of data to improve outcomes for all students. The editor and contributors provide detailed examples of schools that have demonstrated dramatic gains by building collaborative cultures, nurturing ongoing inquiry, and using data systematically. The book shows school leaders how to: Implement collaborative inquiry to meet accountability mandates Build and support a high-performing data culture Establish a school climate characterized by collective responsibility for student learning and a respect for students’ cultures
| Author | : Len Silverston |
| Publisher | : John Wiley & Sons |
| Total Pages | : 572 |
| Release | : 2011-08-08 |
| Genre | : Computers |
| ISBN | : 111808232X |
A quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful 1st Edition, while adding a companion volume to take care of more specific requirements of different businesses. This updated volume provides a common set of data models for specific core functions shared by most businesses like human resources management, accounting, and project management. These models are standardized and are easily replicated by developers looking for ways to make corporate database development more efficient and cost effective. This guide is the perfect complement to The Data Model Resource CD-ROM, which is sold separately and provides the powerful design templates discussed in the book in a ready-to-use electronic format. A free demonstration CD-ROM is available with each copy of the print book to allow you to try before you buy the full CD-ROM.
| Author | : Victoria L. Bernhardt |
| Publisher | : Eye On Education |
| Total Pages | : 122 |
| Release | : 2009 |
| Genre | : Business & Economics |
| ISBN | : 1596671025 |
This book is an easy-to-read primer that describes what it takes to increase student achievement at every grade level, subject area, and student group. Readers will learn how to use data to drive their continuous improvement process as they develop an appreciation of the various types of data, uses for data, and how data are involved with the school improvement process. Online Course Available through a partnerhip with Knowledge Delivery Systems. Click here for more information. (CEUs may be available through your district.)
| Author | : Patricia Pulliam Phillips |
| Publisher | : John Wiley & Sons |
| Total Pages | : 192 |
| Release | : 2008-01-07 |
| Genre | : Business & Economics |
| ISBN | : 0470179015 |
Data Collection Data Collection is the second of six books in the Measurement and Evaluation Series from Pfeiffer. The proven ROI Methodology--developed by the ROI Institute--provides a practical system for evaluation planning, data collection, data analysis, and reporting. All six books in the series offer the latest tools, most current research, and practical advice for measuring ROI in a variety of settings. Data Collection offers an effective process for collecting data that is essential to the implementation of the ROI Methodology. The authors outline the techniques, processes, and critical issues involved in successful data collection. The book examines the various methods of data collection, including questionnaires, interviews, focus groups, observation, action plans, performance contracts, and monitoring records. Written for evaluators, facilitators, analysts, designers, coordinators, and managers, Data Collection is a valuable guide for collecting data that are adequate in quantity and quality to produce a complete and credible analysis.
| Author | : Hadley Wickham |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 521 |
| Release | : 2016-12-12 |
| Genre | : Computers |
| ISBN | : 1491910364 |
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
| Author | : Anna Bernasek |
| Publisher | : Bold Type Books |
| Total Pages | : 258 |
| Release | : 2015-05-26 |
| Genre | : Business & Economics |
| ISBN | : 156858475X |
You don't care who can access your data because you have nothing to hide. But what if corporations were using that data to control your decisions? As millions of consumers carry on unaware, powerful corporations race to collect more and more data about our behaviors, needs, and desires. This massive trove of data represents one of the most valuable assets on the planet. In All You Can Pay, Anna Bernasek and D. T. Mongan show how companies use what they know about you to determine how much you are willing to pay for everything you buy. From college tuition to plane tickets to groceries to medicine, companies already set varying prices based on intimate knowledge of individual wants and purchasing power. As the consumer age fades into history, rapidly changing prices and complex offers tailored to each individual are spreading like a fog over the free market. Data giants know everything about us before we enter stores or open our browsers. We may think that the Internet lets us find the best deals, but the extensive information companies have about us means that the price we see tends toward the maximum they know we can pay. In a momentous shift, the economics of information will turn our economy on its head. Fair bargaining is over.
| Author | : John Paul Mueller |
| Publisher | : John Wiley & Sons |
| Total Pages | : 768 |
| Release | : 2020-01-09 |
| Genre | : Computers |
| ISBN | : 1119626110 |
Your logical, linear guide to the fundamentals of data science programming Data science is exploding—in a good way—with a forecast of 1.7 megabytes of new information created every second for each human being on the planet by 2020 and 11.5 million job openings by 2026. It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time. Get grounded: the ideal start for new data professionals What lies ahead: learn about specific areas that data is transforming Be meaningful: find out how to tell your data story See clearly: pick up the art of visualization Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life—and everyone else’s!
| Author | : John Thompson |
| Publisher | : Simon and Schuster |
| Total Pages | : 190 |
| Release | : 2023-05-23 |
| Genre | : Computers |
| ISBN | : 1633438775 |
Take control of your personal data. Learn how companies manipulate and exploit your data and what you can do to access, delete, and monetize it yourself. Both a handbook and a manifesto, Data for All is a must-read for anyone who wants to take control of their personal data. It lays out how businesses collect, use, and exploit your data, and clearly explains the legislation that will overturn the existing system. Follow John Thompson’s direct and accessible guidance and you’ll completely change your relationship with your data. In this fascinating book, you will learn how to oversee who accesses your data, how much different types of data are worth, and how to keep private details private. You’ll soon stop being a passive source of free data, and start earning a “data dividend”—hundreds or thousands of dollars paid out simply for your daily online activities. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
| Author | : Soumen Chakrabarti |
| Publisher | : Morgan Kaufmann |
| Total Pages | : 477 |
| Release | : 2008-10-31 |
| Genre | : Computers |
| ISBN | : 0080877885 |
This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics ? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology. The proposed book expertly combines the finest data mining material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining. This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources. - Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints. - Presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the reader's technical expertise and ability to implement practical solutions. - Coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases.
