Making Data
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Making Data
For many outside of the scientific community, big data and the forms it takes, such as statistical lists, spreadsheets and graphs, often seem abstract and unintelligible. This book investigates how digital fabrication and traditional making approaches are being used to present data in newly engaging and interesting ways. The first part of the book introduces the basic premise of the data object and the concept of making digital data into a physical form. Contributors cover topics such as biometrics, new technology, the economics of data and open and community uses of data. The second part presents a selection of exemplar forms and contexts for the application of data-objects, such as smart surfaces, smart cities, augmented reality techniques and next generation technical interfaces that blend physical and digital elements. Making Data delivers the importance and likely future prevalence of physical representations of data. It explores the creative methods, processes, theories and cultural histories of making physical representations of information and proposes that the making of data into physical objects is the next important development in the data visualisation phenomenon.
Making Data Visual
Author: Danyel Fisher
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2017-12-20
"You have a mound of data sitting in front of you and a suite of computation tools at your disposal. And yet, you're stumped as to how to turn that data into insight. Which part of that data actually matters, and where is this insight hidden? If you're a data scientist who struggles to navigate the murky space between data and insight, this book will help you think about and reshape data for visual data exploration. It's ideal for relatively new data scientists, who may be computer-knowledgeable and data-knowledgeable, but do not yet know how to create effective, explorable representations of data. With this book, you'll learn: Task analysis, driven by a series of leading questions that draw out the important aspects of the data to be explored; Visualization patterns, each of which take a different perspective on data and answer different questions; A taxonomy of visualizations for common data types; Techniques for gathering design requirements; When and where to make use of statistical methods."--
Making Data Work
If you care about AI transformation, empowering people or advancing organisational success in an increasingly digital world, then you should read this book.—Yomi Ibosiola, Chief Data and Analytics Officer, Union Bank A retail giant already struggling due to the Covid-19 pandemic was faced with a disastrous situation when—at the end of a critical investment in an artificial intelligence project that had been meant to save money—it suddenly discovered that its implementation was likely to leave it worse off. An entire critical service stream within an insurer’s production system crashed. This critical failure resulted in the detentions of fully insured motorists for allegedly not carrying required insurance. Making Data Work: Enabling Digital Transformation, Empowering People and Advancing Organisational Success details these two scenarios as well as others illustrating the consequences that arise when organizations do not know how to make data work properly. It is a journey to determine what to do to "make data work" for ourselves and for our organisations. It is a journey to discover how to bring it all together so organisations can enable digital transformation, empower people, and advance organisational success. It is the journey to a world where data and technology finally live up to the hype and deliver better human outcomes, where artificial intelligence can move us from reacting to situations to predicting future occurrences and enabling desirable possibilities.