Small Data

Author: Martin Lindstrom
Publisher: St. Martin's Press
ISBN: 1466892595
Category : Business & Economics
Languages : en
Pages : 258

Book Description
Martin Lindstrom, a modern-day Sherlock Holmes, harnesses the power of “small data” in his quest to discover the next big thing Hired by the world's leading brands to find out what makes their customers tick, Martin Lindstrom spends 300 nights a year in strangers’ homes, carefully observing every detail in order to uncover their hidden desires, and, ultimately, the clues to a multi-million dollar product. Lindstrom connects the dots in this globetrotting narrative that will enthrall enterprising marketers, as well as anyone with a curiosity about the endless variations of human behavior. You’ll learn... • How a noise reduction headset at 35,000 feet led to the creation of Pepsi’s new trademarked signature sound. • How a worn down sneaker discovered in the home of an 11-year-old German boy led to LEGO’s incredible turnaround. • How a magnet found on a fridge in Siberia resulted in a U.S. supermarket revolution. • How a toy stuffed bear in a girl’s bedroom helped revolutionize a fashion retailer’s 1,000 stores in 20 different countries. • How an ordinary bracelet helped Jenny Craig increase customer loyalty by 159% in less than a year. • How the ergonomic layout of a car dashboard led to the redesign of the Roomba vacuum.

Small Data

Author: Martin Lindstrom Company
Publisher: Hachette UK
ISBN: 1473630150
Category : Business & Economics
Languages : en
Pages : 234

Book Description
The New York Times Bestseller named one of the "Most Important Books of 2016" by Inc, and a Forbes 2016 "Must Read Business Book" 'If you love 'Bones' and 'CSI', this book is your kind of candy' Paco Underhill, author of Why We Buy 'Martin's best book to date. A personal, intuitive, powerful way to look at making an impact with your work' Seth Godin, author of Purple Cow Martin Lindstrom, one of Time Magazine's 100 Most Influential People in The World and a modern-day Sherlock Holmes, harnesses the power of "small data" in his quest to discover the next big thing. In an era where many believe Big Data has rendered human perception and observation 'old-school' or passé, Martin Lindstrom shows that mining and matching technological data with up-close psychological insight creates the ultimate snapshot of who we really are and what we really want. He works like a modern-day Sherlock Holmes, accumulating small clues - the progressively weaker handshakes of Millenials, a notable global decrease in the use of facial powder, a change in how younger consumers approach eating ice cream cones - to help solve a stunningly diverse array of challenges. In Switzerland, a stuffed teddy bear in a teenage girl's bedroom helped revolutionise 1,000 stores - spread across twenty countries - for one of Europe's largest fashion retailers. In Dubai, a distinctive bracelet strung with pearls helped Jenny Craig offset its declining membership in the United States and increase loyalty by 159% in only one year. In China, the look of a car dashboard led to the design of the iRobot, or Roomba, floor cleaner - a great success story. SMALL DATA combines armchair travel with forensic psychology in an interlocking series of international clue-gathering detective stories. It shows Lindstrom using his proprietary CLUES Framework - where big data is merely one part of the overall puzzle - to get radically close to consumers and come up with the counter-intuitive insights that have in some cases helped transform entire industries. SMALL DATA presents a rare behind-the-scenes look at what it takes to create global brands, and reveals surprising and counter-intuitive truths about what connects us all as humans.

Small Wars, Big Data

Author: Eli Berman
Publisher: Princeton University Press
ISBN: 140089011X
Category : Political Science
Languages : en
Pages : 411

Book Description
How a new understanding of warfare can help the military fight today’s conflicts more effectively The way wars are fought has changed starkly over the past sixty years. International military campaigns used to play out between large armies at central fronts. Today's conflicts find major powers facing rebel insurgencies that deploy elusive methods, from improvised explosives to terrorist attacks. Small Wars, Big Data presents a transformative understanding of these contemporary confrontations and how they should be fought. The authors show that a revolution in the study of conflict--enabled by vast data, rich qualitative evidence, and modern methods—yields new insights into terrorism, civil wars, and foreign interventions. Modern warfare is not about struggles over territory but over people; civilians—and the information they might choose to provide—can turn the tide at critical junctures. The authors draw practical lessons from the past two decades of conflict in locations ranging from Latin America and the Middle East to Central and Southeast Asia. Building an information-centric understanding of insurgencies, the authors examine the relationships between rebels, the government, and civilians. This approach serves as a springboard for exploring other aspects of modern conflict, including the suppression of rebel activity, the role of mobile communications networks, the links between aid and violence, and why conventional military methods might provide short-term success but undermine lasting peace. Ultimately the authors show how the stronger side can almost always win the villages, but why that does not guarantee winning the war. Small Wars, Big Data provides groundbreaking perspectives for how small wars can be better strategized and favorably won to the benefit of the local population.

Small Summaries for Big Data

Author: Graham Cormode
Publisher: Cambridge University Press
ISBN: 1108477445
Category : Computers
Languages : en
Pages : 279

Book Description
A comprehensive introduction to flexible, efficient tools for describing massive data sets to improve the scalability of data analysis.

Small Data, Big Disruptions

Author: Martin Schwirn
Publisher: Red Wheel/Weiser
ISBN: 1632657430
Category : Business & Economics
Languages : en
Pages : 228

Book Description
A method to find and connect the small data clues that show what the future’s big picture will look like. “Strategy decisions are like playing high-stakes blackjack, and scanning is the technique for counting cards. Martin Schwirn isn’t a pro gambler, but an expert in scanning.” —Bill Ralston, cofounder of Strategic Business Insights and author of Scenario Planning Handbook An organization’s future success depends on their decision makers’ ability to anticipate changes and disruptions in the marketplace. But how do you get information about tomorrow today? How can your decisions today account for tomorrow’s uncertainties? Small Data, Big Disruptions presents a tool kit to foresee coming changes: Understand why big data will not help you with understanding tomorrow’s disruptions. The future starts with small data—first. Learn the proven 4-step process to capture small data that help envision the future. See examples of how the process anticipated major disruptions. Implement the process in your organization and learn how to initiate meaningful actions. Small Data, Big Disruptions provides the information you need to anticipate the future, understand tomorrow’s market dynamics, and make the necessary decisions to meet the future on your terms. Small Data, Big Disruptions lets you exploit the period between the moment you could know about emerging disruptions and the moment most everybody will know about it. It’s the difference between being ahead of the curve and struggling to catch up.

A Handbook of Small Data Sets

Author: David J. Hand
Publisher: CRC Press
ISBN: 1000064964
Category : Mathematics
Languages : en
Pages : 476

Book Description
This book should be of interest to statistics lecturers who want ready-made data sets complete with notes for teaching.

Big Data, Small Devices

Author: Donna Governor
Publisher:
ISBN: 9781681402765
Category : Big data
Languages : en
Pages : 0

Book Description
Now your students can transform their mobile phones and tablets into tools for learning about everything from weather to water quality. Big Data, Small Devices shows you how. This book is designed for Earth and environmental science teachers who want to help students tap into, organize, and deploy large data sets via their devices to investigate the world around them. Using the many available websites and free apps, students can learn to detect patterns among phenomena related to the atmosphere, biosphere, geosphere, hydrosphere, and seasons. Written by veteran teachers, Big Data, Small Devices is organized into two major parts. It covers tools that help you both find real-time data and understand what to do with the data. Then, the authors provide sample app-based activities that you can use as written or adapt to your specific needs. These days, opportunities to learn are as close as your students' personal technology. As the authors of Big Data, Small Devices note, " Allowing students to conduct investigations using their smart phone in app-based activities allows them to be more engaged in science investigations."

Applications of Big Data in Large- and Small-Scale Systems

Author: Goundar, Sam
Publisher: IGI Global
ISBN: 1799866750
Category : Computers
Languages : en
Pages : 377

Book Description
With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.

Data Analysis with Small Samples and Non-normal Data

Author: Carl F. Siebert
Publisher: Oxford University Press
ISBN: 0199391491
Category : Mathematics
Languages : en
Pages : 241

Book Description
Introduction to nonparametrics -- Analyzing single variables and single groups -- Comparing two or more independent groups -- Comparing two or more related groups -- Predicting with multiple independent variables -- Appendix -- Index

Missing Data and Small-Area Estimation

Author: Nicholas T. Longford
Publisher: Springer Science & Business Media
ISBN: 1846281954
Category : Mathematics
Languages : en
Pages : 357

Book Description
This book evolved from lectures, courses and workshops on missing data and small-area estimation that I presented during my tenure as the ?rst C- pion Fellow (2000–2002). For the Fellowship I proposed these two topics as areas in which the academic statistics could contribute to the development of government statistics, in exchange for access to the operational details and background that would inform the direction and sharpen the focus of a- demic research. After a few years of involvement, I have come to realise that the separation of ‘academic’ and ‘industrial’ statistics is not well suited to either party, and their integration is the key to progress in both branches. Most of the work on this monograph was done while I was a visiting l- turer at Massey University, Palmerston North, New Zealand. The hospitality and stimulating academic environment of their Institute of Information S- ence and Technology is gratefully acknowledged. I could not name all those who commented on my lecture notes and on the presentations themselves; apart from them, I want to thank the organisers and silent attendees of all the events, and, with a modicum of reluctance, the ‘grey ?gures’ who kept inquiring whether I was any nearer the completion of whatever stage I had been foolish enough to attach a date.