Data Driven Print
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| Author | : Patricia Sorce |
| Publisher | : RIT Cary Graphic Arts Press |
| Total Pages | : 196 |
| Release | : 2006 |
| Genre | : Business & Economics |
| ISBN | : 9781933360065 |
Patricia Sorce is the administrative chair of the Rochester Institute of Technology School of Print Media and co-director of the RIT Printing Industry Center. Michael Pletka is manager of Customer Business Development at the Xerox Production Systems Group. Data-Driven Print is their answer to the question of how to overcome the strategic and operational barriers that have impeded growth in this media form by leveraging digital printing technology to deliver customized printed communications. This book, the second volume in the Printing Industry Center Series, documents the current use of personalization and custom communication while identifying the best practices, best prospects, and associated business models for delivering value to printing clients.
| Author | : Patricia A. Sorce |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2009 |
| Genre | : Printing industry |
| ISBN | : 9781933360409 |
Patricia Sorce is the administrative chair of the Rochester Institute of Technology School of Print Media and co-director of the RIT Printing Industry Center. This book, the fourth volume in the Printing Industry Center Series, serves as a follow up to Dr. Sorce's previous book, Data-Driven Print, published in 2006. Here, she documents the importance of utilizing personalization and custom communication techniques, and identifies the best practices, best prospects and associated business models for delivering top value to printing clients. In addition, several case studies provide real-world examples of this evolving industry.
| Author | : Daniel M. Hyson |
| Publisher | : Guilford Publications |
| Total Pages | : 259 |
| Release | : 2020-05-06 |
| Genre | : Psychology |
| ISBN | : 1462543103 |
This indispensable practitioner's guide helps to build the capacity of school psychologists, administrators, and teachers to use data in collaborative decision making. It presents an applied, step-by-step approach for creating and running effective data teams within a problem-solving framework. The authors describe innovative ways to improve academic and behavioral outcomes at the individual, class, grade, school, and district levels. Applications of readily available technology tools are highlighted. In a large-size format for easy photocopying, the book includes learning activities and helpful reproducible forms. The companion website provides downloadable copies of the reproducible forms as well as Excel spreadsheets, PowerPoint slides, and an online-only chapter on characteristics of effective teams. This book is in The Guilford Practical Intervention in the Schools Series, edited by Sandra M. Chafouleas.
| Author | : Thomas C. Redman |
| Publisher | : Harvard Business Press |
| Total Pages | : 273 |
| Release | : 2008-09-22 |
| Genre | : Business & Economics |
| ISBN | : 1422163644 |
Your company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making. In Data Driven, Thomas Redman, the "Data Doc," shows how to leverage and deploy data to sharpen your company's competitive edge and enhance its profitability. The author reveals: · The special properties that make data such a powerful asset · The hidden costs of flawed, outdated, or otherwise poor-quality data · How to improve data quality for competitive advantage · Strategies for exploiting your data to make better business decisions · The many ways to bring data to market · Ideas for dealing with political struggles over data and concerns about privacy rights Your company's data is a key business asset, and you need to manage it aggressively and professionally. Whether you're a top executive, an aspiring leader, or a product-line manager, this eye-opening book provides the tools and thinking you need to do that.
| Author | : Rajkumar Venkatesan |
| Publisher | : University of Virginia Press |
| Total Pages | : 278 |
| Release | : 2021-01-13 |
| Genre | : Business & Economics |
| ISBN | : 081394516X |
The authors of the pioneering Cutting-Edge Marketing Analytics return to the vital conversation of leveraging big data with Marketing Analytics: Essential Tools for Data-Driven Decisions, which updates and expands on the earlier book as we enter the 2020s. As they illustrate, big data analytics is the engine that drives marketing, providing a forward-looking, predictive perspective for marketing decision-making. The book presents actual cases and data, giving readers invaluable real-world instruction. The cases show how to identify relevant data, choose the best analytics technique, and investigate the link between marketing plans and customer behavior. These actual scenarios shed light on the most pressing marketing questions, such as setting the optimal price for one’s product or designing effective digital marketing campaigns. Big data is currently the most powerful resource to the marketing professional, and this book illustrates how to fully harness that power to effectively maximize marketing efforts.
| Author | : Rado Kotorov |
| Publisher | : Business Expert Press |
| Total Pages | : 169 |
| Release | : 2020-04-21 |
| Genre | : Business & Economics |
| ISBN | : 195152781X |
Today the fastest growing companies have no physical assets. Instead, they create innovative digital products and new data-driven business models. They capture huge market share fast and their capitalizations skyrocket. The success of these digital giants is pushing all companies to rethink their business models and to start digitizing their products and services. Whether you are a new start-up building a digital product or service, or an employee of an established company that is transitioning to digital, you need to consider how digitization has transformed every aspect of management. Data-driven business models scale not through asset accumulation and product standardization, but through disaggregation of supply and demand. The winners in the new economy master the demand for one and the supply to millions. Throughout the book the author illustrates with examples and use cases how the market competition has changed and how companies adept to the new rules of the game. The economic levers of scale and scope are also different in the digital economy and companies have to learn new tactics how to achieve and sustain their competitive advantage. While data is at the core of all digital business models, the monetization strategies vary across products, services and business models. Our Monetization Matrix is a model that helps managers, marketers, sales professionals, and technical product designers to align the digital product design with the data-driven business model.
| Author | : Steven L. Brunton |
| Publisher | : Cambridge University Press |
| Total Pages | : 615 |
| Release | : 2022-05-05 |
| Genre | : Computers |
| ISBN | : 1009098489 |
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
| Author | : Paul Bambrick-Santoyo |
| Publisher | : John Wiley & Sons |
| Total Pages | : 336 |
| Release | : 2010-04-12 |
| Genre | : Education |
| ISBN | : 0470548746 |
Offers a practical guide for improving schools dramatically that will enable all students from all backgrounds to achieve at high levels. Includes assessment forms, an index, and a DVD.
| Author | : Nathalie Henry Riche |
| Publisher | : CRC Press |
| Total Pages | : 376 |
| Release | : 2018-03-28 |
| Genre | : Computers |
| ISBN | : 1315281554 |
This book presents an accessible introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, it offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners.
| Author | : Bernard J. Jansen |
| Publisher | : Springer Nature |
| Total Pages | : 317 |
| Release | : 2022-05-31 |
| Genre | : Computers |
| ISBN | : 3031022319 |
Data-driven personas are a significant advancement in the fields of human-centered informatics and human-computer interaction. Data-driven personas enhance user understanding by combining the empathy inherent with personas with the rationality inherent in analytics using computational methods. Via the employment of these computational methods, the data-driven persona method permits the use of large-scale user data, which is a novel advancement in persona creation. A common approach for increasing stakeholder engagement about audiences, customers, or users, persona creation remained relatively unchanged for several decades. However, the availability of digital user data, data science algorithms, and easy access to analytics platforms provide avenues and opportunities to enhance personas from often sketchy representations of user segments to precise, actionable, interactive decision-making tools—data-driven personas! Using the data-driven approach, the persona profile can serve as an interface to a fully functional analytics system that can present user representation at various levels of information granularity for more task-aligned user insights. We trace the techniques that have enabled the development of data-driven personas and then conceptually frame how one can leverage data-driven personas as tools for both empathizing with and understanding of users. Presenting a conceptual framework consisting of (a) persona benefits, (b) analytics benefits, and (c) decision-making outcomes, we illustrate applying this framework via practical use cases in areas of system design, digital marketing, and content creation to demonstrate the application of data-driven personas in practical applied situations. We then present an overview of a fully functional data-driven persona system as an example of multi-level information aggregation needed for decision making about users. We demonstrate that data-driven personas systems can provide critical, empathetic, and user understanding functionalities for anyone needing such insights.
