Bursting The Big Data Bubble

As we get caught up in the quagmire of Big Data and analytics, it remains critically important to be able to reflect and apply insights, experience, and intuition to your decision-making process. In fact, a recent research study at Tel Aviv University found that executives who relied on their intuition were 90 percent accurate in their decisions.Bu

As we get caught up in the quagmire of Big Data and analytics, it remains critically important to be able to reflect and apply insights, experience, and intuition to your decision-making process. In fact, a recent research study at Tel Aviv University found that executives who relied on their intuition were 90 percent accurate in their decisions. Bursting the Big Data Bubble: The Case for Intuition-Based Decision Making focuses on this intuition-based decision making. The book does not discount data-based decision making, especially for decisions that are important and complex. Instead, it emphasizes the importance of applying intuition, gut feel, spirituality, experiential learning, and insight as key factors in the executive decision-making process. Explaining how intuition is a product of past experience, learning, and ambient factors, the text outlines methods that will help to enhance your data-driven decision-making process with intuition-based decision making. The first part of the book, the "Research Track", presents contributions from leading researchers worldwide on the topic of intuition-based decision making as applied to management. In the second part of the book, the "Practice Track," global executives and senior managers in industry, government, universities, and not-for-profits present vignettes that illustrate how they have used their intuition in making key decisions. The research part of the book helps to frame the problem and address leading research in intuition-based decision making. The second part then explains how to apply these intuition-based concepts and issues in your own decision-making process.

Lead your organization into the industrial revolution of analytics with The Analytics Revolution The topics of big data and analytics continue to be among the most discussed and pursued in the business world today. While a decade ago many people still questioned whether or not data and analytics would help improve their businesses, today virtually no one questions the value that analytics brings to the table. The Analytics Revolution focuses on how this evolution has come to pass and explores the next wave of evolution that is underway. Making analytics operational involves automating and embedding analytics directly into business processes and allowing the analytics to prescribe and make decisions. It is already occurring all around us whether we know it or not. The Analytics Revolution delves into the requirements for laying a solid technical and organizational foundation that is capable of supporting operational analytics at scale, and covers factors to consider if an organization is to succeed in making analytics operational. Along the way, you'll learn how changes in technology and the business environment have led to the necessity of both incorporating big data into analytic processes and making them operational. The book cuts straight through the considerable marketplace hype and focuses on what is really important. The book includes: An overview of what operational analytics are and what trends lead us to them Tips on structuring technology infrastructure and analytics organizations to succeed A discussion of how to change corporate culture to enable both faster discovery of important new analytics and quicker implementation cycles of what is discovered Guidance on how to justify, implement, and govern operational analytics The Analytics Revolution gives you everything you need to implement operational analytic processes with big data.

This book contains the refereed proceedings of the 17th International Conference on Business Information Systems, BIS 2014, held in Larnaca, Cyprus, in May 2014. The BIS conference series follows trends in academic and business research; thus, the theme of the BIS 2014 conference was “Big Data: Problems Solved and Remaining Challenges.” Currently, big data is one of the most prominent trends in areas such as recommendation engines, fraud detection, risk modeling, marketing campaign and social network analysis. The 22 revised full papers were carefully reviewed and selected from 58 submissions. They are grouped into sections on big data, business process management, ontologies and conceptual modeling, collaboration, service science and interoperability and specific BIS applications.

​This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning​. Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems. The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns​.

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.

Its scale, flexibility, cost effectiveness, and fast turnaround are just a few reasons why crowdsourced testing has received so much attention lately. While there are a few online resources that explain what crowdsourced testing is all about, there's been a need for a book that covers best practices, case studies, and the future of this technique. Filling this need, Leveraging the Wisdom of the Crowd in Software Testing shows you how to leverage the wisdom of the crowd in your software testing process. Its comprehensive coverage includes the history of crowdsourcing and crowdsourced testing, implementation practices, and future trends. The book discusses best practices in implementation-explaining what, when, and how to crowdsource in a testing effort. It also includes case studies that illustrate how both product and service companies have successfully applied crowdsourcing in their testing programs. Explaining how to use the combined advantages of crowdsourcing and cloud computing for software testing, the book examines various engagement models in which you could implement crowdsourced testing. It addresses effective defect management in crowdsourced testing and considers both the business and engineering aspects of crowdsourced testing. The book explores the challenges, limitations, and situations when crowdsourced testing will not work and provides powerful best practices for mitigating the constraints and challenges, including how to build a crowdsourcing platform to test software products. Covering career opportunities for crowd testers, the book concludes by taking a look at the need to build a crowdsourced testing ecosystem, who the players of such an ecosystem would be, and who would need to champion such an effort.

An in-depth look at the intersection of judgment and statistics in baseball Scouting and scoring are considered fundamentally different ways of ascertaining value in baseball. Scouting seems to rely on experience and intuition, scoring on performance metrics and statistics. In Scouting and Scoring, Christopher Phillips rejects these simplistic divisions. He shows how both scouts and scorers rely on numbers, bureaucracy, trust, and human labor to make sound judgments about the value of baseball players. Tracing baseball’s story from the nineteenth century to today, Phillips explains that the sport was one of the earliest fields to introduce numerical analysis, and new methods of data collection were supposed to enable teams to replace scouting with scoring. But that’s not how things turned out. From the invention of official scorers and Statcast to the creation of the Major League Scouting Bureau, Scouting and Scoring reveals the inextricable connections between human expertise and data science, and offers an entirely fresh understanding of baseball.