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Erschienen in:
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2014 | OriginalPaper | Buchkapitel

1. Big Data

verfasst von : Vincenzo Morabito

Erschienen in: Trends and Challenges in Digital Business Innovation

Verlag: Springer International Publishing

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Abstract

The role of this Chapter is to introduce the reader to the area of Big Data, one of the IT trends actually emerging as strategic for companies competing in current digital global market. The Chapter aims to clarify the main drivers and characteristics of Big Data, both at technical and managerial level. Furthermore, the Chapter aims at investigating management challenges and opportunities, identifying the main phases and actions of a Big Data lifecycle. Finally, the discussion of case studies concludes the Chapter, providing insights from practice on factors and strategic points of attention, suitable to support Big Data-driven decision making and operational performance.

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Nächstes Kapitel Cloud Computing
Fußnoten
1
In the following we use data when we refer to raw, unstructured facts that need to be stored and processed by an information system, in order to be meaningful and useful for an agent (being human or else a machine). Whereas we call information the useful and meaningful output of information systems, being the data processed, organized, structured, and presented. Thus, adopting the General Definition of Information (GDI) we could define information “data + meaning” [35]. It is worth noting that computer based information systems are a specific type of information system and not exhaustive [36]. For a systematic survey on the different definitions, meanings and use of information we kindly refers the reader to [35, 37].
 
2
Using an iPhone app to request money from a nearby Automatic Teller Machine (ATM), scanning the phone to retrieve the bill. This is an example of a Generation Z like evolution of ATM design towards a convergence with online and mobile banking, with a consequent change in the volume and variety of data to be managed by banks and financial services providers. Furthermore, it shows how, e.g., finance sector competition is facing the challenge of PayPal and Google Wallet diffusion and adoption by digital natives. “We think we’ll attract a new client base, 35 and under, we didn’t cater to before” said Thomas Ormseth, Senior Vice President of Wintrust Financial in an article appeared in July 2013 on Bloomberg Businessweek [38].
 
3
Several classifications of the NoSQL databases have been proposed in literature [39]. Here we mention Key-/Value-Stores (a map/dictionary allows clients to insert and request values per key) and Column-Oriented databases (data are stored and processed by column instead of row). An example of the former is Amazon’s Dynamo; whereas HBase, Google’s Bigtable, and Cassandra represent Column-Oriented databases. For further details we refer the reader to [39, 40].
 
4
MapReduce exploit, on the one hand, (i) a map function, specified by the user to process a key/value pair and to generate a set of intermediate key/value pairs; on the other hand, (ii) a reduce function that merges all intermediate values associated with the same intermediate key [41]. MapReduce has been used to rewrite the production indexing system that produces the data structures used for the Google web search service [41].
 
5
See for example how IBM has exploited/integrated Hadoop [42].
 
6
“The reason is you can’t find the talent, you can’t maintain it, and so on. We believe this idea of reuse is going to differentiate the winners from the losers.” Ruh, reported by Consultancy (2013).
 
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Metadaten
Titel
Big Data
verfasst von
Vincenzo Morabito
Copyright-Jahr
2014
Buch
Trends and Challenges in Digital Business Innovation

Print ISBN: 978-3-319-04306-7

Electronic ISBN: 978-3-319-04307-4

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-3-319-04307-4_1