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Data Control. Jean-Louis MoninoЧитать онлайн книгу.

Data Control - Jean-Louis Monino


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one. In particular I offer my thanks to Philippe RIBIERE, President of E2S-Conseils with whom I have written several R&D books over the years.

      Thank you also to the team of researchers at the “Montpellier Recherche en Economie” laboratory who demonstrated their trust in my research and granted me my emeritus status.

      To my grandchildren: Lily-Rose, Jean-Baptiste, Alice and Gabriel.

      To Anne-Marie, my wife.

      Jean-Louis MONINO

      Introduction

      The world has become digital, and technological advances have increased the number of different ways for accessing, processing, and distributing data. New technologies are now reaching a certain maturity.

      This phenomenon is now of interest to operational decision-makers (marketing managers, financial managers, etc.) when it comes to analyzing the immense potential of data held by companies in real-time. In order to meet the challenge of “Big Data”, measures should be taken that include all the tools that allow data to be processed in a more restrictive way, as well as all the actors who analyze these data. This will only be possible through an awareness of the gains offered by “data enhancement”. The data in the organized, reorganized bases, processed by statistical methods or econometric modeling, become knowledge.

      For a company it is essential to have more and more data about the environment in which it operates or will operate. We will no longer work on classes of behaviors but on individual analysis. It is easy to understand that this revolution is leading to the creation of so-called “start-up” companies whose aim is the automatic processing of data that make up what is known as “Big Data”. This is certainly one of the components of what some call the “new industrial revolution”. The Internet, digital and connected objects have opened up new horizons in a multitude of fields.

      As an example, access to data allows quantitative and qualitative analyses to be enriched. Customer contacts can be analyzed with data collected by a call center1; this kind of product can also be offered in limited numbers, as E2S-Conseils does. This needs to be developed by exploring the content of emails, voice calls, and mixing this information with website navigation. Or, study the messages exchanged on social networks (Facebook, Twitter, Linkedin, etc.) to identify interesting new products or to know which products are most talked about.

      For data to reach its full value potential, it must be easily accessible to all interested parties without additional barriers and at economically bearable costs. If the data are open to users (Matouk - MTRL review), other specific data processing companies may be created. This activity will meet the needs of users without the need for them to build models and equations themselves. 1

      To limit itself to the economic benefits of open data, a study carried out for the European Commission estimated the total public sector information market in 2008 in the EU at 28 billion euros. According to this study, the overall economic benefits of more open public sector data would amount to about 40 billion euros per year for the EU. For the EU economy as a whole, the total direct and indirect economic gains from the use of ISPs (Internet Service Providers) and applications based on these data would be in the order of 140 billion euros per year.

      The Internet age has massively increased the search for information. Companies are overwhelmed by the flood of data that results from simply surfing the Internet. In other words, they are forced to acquire the relevant information to develop their high value-added strategies in order to master the ever-changing environment. Now, the management of industrial strategies is largely based on the ability of companies to access strategic information to better develop their environment. This information can therefore be the source of new knowledge (knowledge pyramid).

      The process of collecting, processing and interpreting information is a practice that goes beyond the definition of ideas to the realization of those ideas to ensure a better production of knowledge that generates innovations. It is economic intelligence that enables each company to optimize its offer quantitatively and qualitatively and also to optimize its production technologies.

      In addition to the advent of ICT, the speed of production, dissemination and data processing capacity, another element has become important in recent years: time. This temporal element implies a notion of speed of information flow. This calls for a rethinking of corporate strategy, beyond the difficulties posed by the processing of large volumes of data. The value of a data item increases over time and depends on the multiple uses that are made of it.

      Figure I.1. Digital golden jobs in 2018. For a color version of this figure, see www.iste.co.uk/monino/control.zip

      For some professions, the jump will be very high. According to Robert Half, the “golden job” in the digital world will be that of SEO Manager with 5-10 years of experience: the remuneration linked to this job should increase by 27% compared to 2017 and reach between 65,000 and 90,000 euros per year. Data scientists, even with little experience, will also see their salaries increase by 22%.

      Figure I.2. TIBCO's data mining and Statistica software. The research and development project of E2S-Conseils in collaboration with the TRIS laboratory has been developed using Tibco's Statistica Data Mining for health research (MONINO L., TIBCO's data mining and Statistica


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