101 Lightbulb Moments In Data Management

A collection of the best contributions from DataFlux's featured experts.

The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You’ll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. You’ll come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies. Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challenges Enables discussions between business and IT with a non-technical vocabulary for data quality measurement Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation

Residents in Boston, Massachusetts are automatically reporting potholes and road hazards via their smartphones. Progressive Insurance tracks real-time customer driving patterns and uses that information to offer rates truly commensurate with individual safety. Google accurately predicts local flu outbreaks based upon thousands of user search queries. Amazon provides remarkably insightful, relevant, and timely product recommendations to its hundreds of millions of customers. Quantcast lets companies target precise audiences and key demographics throughout the Web. NASA runs contests via gamification site TopCoder, awarding prizes to those with the most innovative and cost-effective solutions to its problems. Explorys offers penetrating and previously unknown insights into healthcare behavior. How do these organizations and municipalities do it? Technology is certainly a big part, but in each case the answer lies deeper than that. Individuals at these organizations have realized that they don't have to be Nate Silver to reap massive benefits from today's new and emerging types of data. And each of these organizations has embraced Big Data, allowing them to make astute and otherwise impossible observations, actions, and predictions. It's time to start thinking big. In Too Big to Ignore, recognized technology expert and award-winning author Phil Simon explores an unassailably important trend: Big Data, the massive amounts, new types, and multifaceted sources of information streaming at us faster than ever. Never before have we seen data with the volume, velocity, and variety of today. Big Data is no temporary blip of fad. In fact, it is only going to intensify in the coming years, and its ramifications for the future of business are impossible to overstate. Too Big to Ignore explains why Big Data is a big deal. Simon provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data. Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, the book is required reading for chief executives, company owners, industry leaders, and business professionals.

Winner of the 2016 De Groot Prize from the International Society for Bayesian AnalysisNow in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied

If you want your startup to succeed, you need to understand why startups fail. “Whether you’re a first-time founder or looking to bring innovation into a corporate environment, Why Startups Fail is essential reading.”—Eric Ries, founder and CEO, LTSE, and New York Times bestselling author of The Lean Startup and The Startup Way Why do startups fail? That question caught Harvard Business School professor Tom Eisenmann by surprise when he realized he couldn’t answer it. So he launched a multiyear research project to find out. In Why Startups Fail, Eisenmann reveals his findings: six distinct patterns that account for the vast majority of startup failures. • Bad Bedfellows. Startup success is thought to rest largely on the founder’s talents and instincts. But the wrong team, investors, or partners can sink a venture just as quickly. • False Starts. In following the oft-cited advice to “fail fast” and to “launch before you’re ready,” founders risk wasting time and capital on the wrong solutions. • False Promises. Success with early adopters can be misleading and give founders unwarranted confidence to expand. • Speed Traps. Despite the pressure to “get big fast,” hypergrowth can spell disaster for even the most promising ventures. • Help Wanted. Rapidly scaling startups need lots of capital and talent, but they can make mistakes that leave them suddenly in short supply of both. • Cascading Miracles. Silicon Valley exhorts entrepreneurs to dream big. But the bigger the vision, the more things that can go wrong. Drawing on fascinating stories of ventures that failed to fulfill their early promise—from a home-furnishings retailer to a concierge dog-walking service, from a dating app to the inventor of a sophisticated social robot, from a fashion brand to a startup deploying a vast network of charging stations for electric vehicles—Eisenmann offers frameworks for detecting when a venture is vulnerable to these patterns, along with a wealth of strategies and tactics for avoiding them. A must-read for founders at any stage of their entrepreneurial journey, Why Startups Fail is not merely a guide to preventing failure but also a roadmap charting the path to startup success.

The fun and simple problem-solving guide that took Japan by storm Ken Watanabe originally wrote Problem Solving 101 for Japanese schoolchildren. His goal was to help shift the focus in Japanese education from memorization to critical thinking, by adapting some of the techniques he had learned as an elite McKinsey consultant. He was amazed to discover that adults were hungry for his fun and easy guide to problem solving and decision making. The book became a surprise Japanese bestseller, with more than 370,000 in print after six months. Now American businesspeople can also use it to master some powerful skills. Watanabe uses sample scenarios to illustrate his techniques, which include logic trees and matrixes. A rock band figures out how to drive up concert attendance. An aspiring animator budgets for a new computer purchase. Students decide which high school they will attend. Illustrated with diagrams and quirky drawings, the book is simple enough for a middleschooler to understand but sophisticated enough for business leaders to apply to their most challenging problems.

“A Way to Garden prods us toward that ineffable place where we feel we belong; it’s a guide to living both in and out of the garden.” —The New York Times Book Review For Margaret Roach, gardening is more than a hobby, it’s a calling. Her unique approach, which she calls “horticultural how-to and woo-woo,” is a blend of vital information you need to memorize and intuitive steps you must simply feel and surrender to. In A Way to Garden, Roach imparts decades of garden wisdom on seasonal gardening, ornamental plants, vegetable gardening, design, gardening for wildlife, organic practices, and much more. She also challenges gardeners to think beyond their garden borders and to consider the ways gardening can enrich the world. Brimming with beautiful photographs of Roach’s own garden, A Way to Garden is practical, inspiring, and a must-have for every passionate gardener.

This book explores the science behind intuitive decision-making in business, and shows how people's innate capacity for intuition can be nurtured and strengthened to maximize performance. We are all familiar with those perplexing situations when we think we 'just know' without knowing how or why we know. In professional life it might be the job candidate's CV that checks all the boxes but somehow doesn't stack-up: should we perform some due diligence and dig a little deeper? In personal life it could be the apartment that we're looking to rent that just felt right the minute we walked through the front door: should we trust our hunch and grab it while we can? What if time is of the essence? What if there isn't any more data to be had in the time available? In this volume, Eugene Sadler-Smith examines why situations like these often leave us in a quandary, and why these decisions so often leave us in two minds. He reveals that metaphorically speaking, we have two minds in one brain: an 'analytical mind' and an 'intuitive mind', which sometimes come to quite different conclusions about what we ought to do in those consequential decisions that permeate our professional and personal lives. Rather than thinking of our intuitive and analytical minds in constant battle with each other, we might instead think of them as two information-processing systems that have evolved to complement each other. The main idea of this book is that our analytical mind evolved to 'solve' whilst our intuitive mind evolved to 'sense'. Neither is infallible, and our intuitions can be both flawed and marvellous at the same time. The author's clear and detailed explanation of the science behind intuition reveals how we can make intelligent use of our intuition to sense and solve our way through a world that is fast-moving, complex, and uncertain.