The Path to Manageable Data - Going Beyond the Three V’s of Big Data
Big data Abstract
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REPÚBLICA BOLIVARIANA DE VENEZUELA
MINISTERIO DEL PODER POPULAR PARA LA DEFENSA
UNIVERSIDAD NACIONAL EXPERIMENTAL POLITÉCNICA
DE LA FUERZA ARMADA NACIONAL
DECANATO NÚCLEO - CARACAS
UNIDAD ACADÉMICA
EQUIPO DE ALTO DESEMPEÑO DE POSTGRADO
STRATEGIC MANAGEMENT OF BIG DATA INNOVATIVE BUSINESS MODELS
AT CANTV TV OPERATIONS DEPARTMENT (GOTV)
Author: Liodegar Bracamonte.
Supervisor: Lic. Orlando Cánchica, M.Sc.
Date: September, 2014.
RESUMEN EN INGLÉS
ABSTRACT
The digital activity of modern society has promoted a rapid growth in the volume of
generated data. All this huge volume of data, is what the ICT industry has called Big
Data, and refers to the set of data for its variety, volume and velocity of generation
(3V) exceeds the capacity of traditional data management. Among the organizations
that should tackle this new trend of data, are those of the telecommunications sector,
where Cantv is framed as the company object of study. Cantv daily has to manage
large volumes of data, which do not converge in real time to optimize the user
experience. In this situation, a holistic approach to the strategic management of Big
Data is proposed to identify potential opportunities to create value by leveraging
innovative business models. The type of approach used to develop the investigation
was qualitative research, using an action research design of practical type, which
followed a flexible and iterative process. Qualitative analysis involved organizing the
collected data and code to extract a first level, meaning units and categories; and on
a second level, themes and relationships between concepts, to eventually generate
explanations of the data which were processed and evaluated in-depth. By using the
basis of these explanations and existing approaches to managing Big Data, an
approach of strategic management of Big Data to leverage innovative business
models adapted to the corporate reality of Cantv, was proposed.
Keywords: Strategic management, Big Data, business models, innovation, value
creation.