From Big Data to Smart Data E-Book

Fernando Iafrate

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 75

Veröffentlichungsjahr: 2015

Beschreibung

A pragmatic approach to Big Data by taking the reader on a journey between Big Data (what it is) and the Smart Data (what it is for).

Today’s decision making can be reached via information (related to the data), knowledge (related to people and processes), and timing (the capacity to decide, act and react at the right time). The huge increase in volume of data traffic, and its format (unstructured data such as blogs, logs, and video) generated by the “digitalization” of our world modifies radically our relationship to the space (in motion) and time, dimension and by capillarity, the enterprise vision of performance monitoring and optimization.

Leseprobe

Contents

Preface

List of Figures and Tables

LIST OF FIGURES

LIST OF TABLE S

Introduction

I.1. Objectives

I.2. Observation

I.3. In sum

1 What is Big Data?

1.1. The four “V”s characterizing Big Data

1.2. The technology that supports Big Data

2 What is Smart Data?

2.1. How can we define it?

2.2. The structural dimension

2.3. The closed loop between Big Data and Smart Data

3 Zero Latency Organization

3.1. From Big Data to Smart Data for a zero latency organization

3.2. Three types of latency

4 Summary by Example

4.1. Example 1: date/product/price recommendation

4.2. Example 2: yield/revenue management (rate controls)

4.3. Example 3: optimization of operational performance

Conclusion

Bibliography

Glossary

Index

First published 2015 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUK

www.iste.co.uk

John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USA

www.wiley.com

© ISTE Ltd 2015

The rights of Fernando Iafrate to be identified as the author of this work have been asserted by him in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Control Number: 2015930755

British Library Cataloguing-in-Publication DataA CIP record for this book is available from the British LibraryISBN 978-1-84821-755-3

Preface

This book offers a journey through the new informational “space–time” that is revolutionizing the way we look at information through the study of Big and Smart Data for a zero-latency-connected world, in which the ability to act or react (in a pertinent and permanent way), regardless of the spatiotemporal context of our digitized and connected universe, becomes key.

Data (elementary particles of information) are constantly in motion (the Internet never sleeps), and once it is filtered, sorted, organized, analyzed, presented, etc., it feeds a continuous cycle of decision-making and actions. Crucial for this are the relationships between the data (their characteristics, format, temporality, etc.) and their value (ability to analyze and integrate it into an operational cycle of decision-making and actions), whether it is monitored by a “human” or an “automated” process (via software agents and other recommendation engines).

The world is in motion, and it will continue to move at an increasingly faster pace. Businesses must keep up with this movement and not fall behind (their competitiveness depends on it): the key to doing so is understanding and becoming an expert on the economic environment, which since the advent of the internet has become global.

Big Data was created relatively recently (less than five years ago) and is currently establishing itself in the same way Business Intelligence (technical and human methods for managing internal and external business data to improve competiveness, monitoring, etc.) established itself at the beginning of the new millennium. The huge appetite for Big Data (which is, in fact, an evolution of Business Intelligence and cannot be dissociated from it) is due to the fact that businesses, by implementing Business Intelligence solutions and organizations, have become very skilled at using and valuing their data, whether it is for strategic or operational ends. The advent of “cloud computing” (capacity enabling technological problems to be resolved by a third party) enables businesses (small- and medium-sized businesses now also have access to these tools, whereas they were previously the reserve of the large companies that could afford them) to facilitate and accelerate the implementation of Big Data. Following its rapid expansion in the early 2000s, Business Intelligence has been looking to reinvent itself; Big Data is establishing itself in this world as an important vector for growth. With the exponential “digitization” (via the Internet) of our world, the volume of available data is going through the roof (navigation data, behavioral data, customer preferences, etc.). For those who know how to use it, this data represents value and is a real advantage for getting one step ahead of the competition.

This move forward promises zero latency and connected businesses where each “event” (collected by data) can be tracked, analyzed and published to monitor and optimize businesses processes (for strategic or operational ends). This occurs when the two worlds managing the data meet: the transactional world (that aims to automate operational business processes) and the decision-making world (a medium for monitoring and optimizing business processes). For a long time, these two worlds were separated by the barriers of data “temporality” and “granularity”. The transactional world has a temporality of a millisecond, or even less for data processing that supports operational business processes, whereas the decision-making world has a temporality of several hours and in some cases even days due to the volumes, diverse and varied sources, and consolidation and aggregation necessities, etc., of data. It will be seen that using all (operational and decision-making) data is required to support decision-making processes.

Unifying the decision-making world and the transactional world will require businesses to rethink their information system so as to increase its interoperability (capacity to integrate with other systems) and to improve the temporality of the management of the data flows it exchanges. This is known as an event-driven architecture (EDA), and it enables normalized and no latency data to be exchanged between its components. The information system’s use value can therefore be improved.

Fernando IAFRATEFebruary 2015