After a long phase of experimentation, Big Data has now entered a phase of daily use by many firms in most industries. To demonstrate the relevance and importance of this new technology in the enterprise, Business&Decision presents a white paper entitled “From Big Data to Big Business”.
Contrary to the majority of literature on the subject of Big Data, Business&Decision does not wish to expand on the difficulties encountered by companies in the face of the increase in the volume of data to be analysed. Conversely, the objective of this white paper is to help marketing, finance, management, R&D or logistics professionals to understand how to operate the possibilities offered by the Big Data.
This book is divided into seven chapters The following topics are covered: the principles of Big Data, data, new uses of Big Data, architectures and algorithms, the business of Big Data, the dangers of Big Data for privacy and finally the transition from Big Data to Big Business.
In the first part of this white paper, Business&Decision attempts to determine whether Big Data is a simple fad or a real tool for improvement performance for companies.
Throughout the first chapter, the authors recall the context and founding principles from the Big Data. This phenomenon is defined here as a new discipline at the crossroads of statistics, databases, technology and business.
In the eyes of Business&Decision, its emergence is linked to the exponential increase in the volume of data and its complexity. Big Data is about collecting, analyzing and exploiting this data efficiently and quickly using new tools to gain competitive advantage.
The book then returns to the origins of Big Data. Used for the first time by Gartner in 2008However, the term refers to a concept that was announced at the very beginning of computer science. The data explosion was announced as early as 2001 with the first mention of 3V (volume, velocity, variety). Similarly, this phenomenon is a result of the Data MiningThis is at the crossroads of statistics and artificial intelligence, a trend that dates back to around 1995.
However, for Business&Decision, the true origin of Big Data is, in agreement with O’Reilly, linked to the development of e-commerce. The large volume of data generated by Internet users on e-commerce sites such as Amazon or eBay has enabled the development of new technologies to respond in real time to user needs. This phenomenon was later named Big Data.
To conclude this first chapter, the specificities of Big Data are classified into four themes: data, uses, working methods and tools. Finally, the authors explain that a Big Data project must be built around four components : technology, methodology, legal and social.
In the rest of the book, chapter 2 returns to data, the main element of the Big Data. First, we talk about the famous 3V (Volume, Speed, Variety), then about their evolution, the 5V and the 3P. The book then discusses the difference between data and information, and how the accumulated data has made sense over time.
Chapter 3 concerns uses induced by Big Data, such as a new look at data archives, internal and external data proliferation, open data and data monetization.
Chapter 4 then discusses the architectures and algorithms related to Big Data, be it hardware, software or databases and the tools to analyze them. Chapter 5 details the jobs created by the Big Dataand provides advice on practising these professions.
Finally, chapter 6 asks about the possible nuisance of Big Data and the data race vis-à-vis consumer privacy and businesses. The last chapter provides a balance sheet by detailing in 10 key points how to convert Big Data to “Big Business”.
To download the white paper If you would like to receive the “From Big Data to Big Business$$” by Business&Decision, please fill in the form at this address. You can consult the first chapter through this extract available on Slideshare: White Paper “From Big Data to Big Business”.