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Diseño e implementación de una infraestructura Big Data para análisis de mercados financieros

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2016-07
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2016-07-05
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Smartphones, wearables, sensores y todo tipo de empresas y organizaciones generan millones de datos al día. De la necesidad de la organización y el procesado de esos datos surge el término Big Data, a través del cual podemos realizar dichas tareas de una manera rápida y eficiente, que con las herramientas de procesado existentes hasta el momento no hubiera sido posible. El mundo del Big Data ha crecido enormemente en los últimos años, tanto en volumen de negocio como en herramientas disponibles para su desarrollo, permitiendo grandes avances y creando un sector completamente nuevo. Son muchas las empresas que recurren a estas nuevas tecnologías para obtener resultados de grandes conjuntos de datos, ya que el propio dato es el que contiene un valor oculto, que solo aparece al haber sido procesado, dotándolo de sentido. La importancia de la economía en la vida de las personas es muy grande, a través de los mercados financieros se manejan los flujos de capitales de los inversores que apuestan por las grandes empresas, modificando el funcionamiento de los mercados bursátiles y por tanto de la economía. De la necesidad del análisis de los datos procedentes de esos mercados y aprovechando las ventajas del Big Data, en este trabajo de fin de grado se han querido conjugar ambos campos con el objetivo de obtener herramientas de inversión predictivas en un sistema eficaz, eficiente, rápido y escalable, adaptándose a diferentes escenarios. Para la consecución de los objetivos fijados se han empleado dos tecnologías utilizadas en el mundo Big Data, Hadoop y Hive, las cuáles, y como se verá a lo largo de este proyecto, nos proporcionan las herramientas necesarias para el tratado y procesado de datos. Una vez finalizado el proyecto, se podrá recabar información de diferentes mercados financieros, introducirlos en el sistema Big Data diseñado para su procesamiento y análisis a partir de algoritmos de inversión, los cuáles nos aportaran una serie de resultados. Además, contaremos con diferentes alternativas de diseño, todas ellas orientadas a satisfacer necesidades provenientes de diferentes posibilidades de uso.
Smartphones, wearables, sensors and all type of companies and organizations generate countless amounts of data per day. From the need for these companies to process such a massive amount of data, the term and concept of Big Data has been created. The new Big Data systems allow a faster and more efficient data processing in comparison to the traditional processing tools that existed and were available in the market until now. Big Data has grown tremendously in the last few years, both in terms of volume of operations and business revenue as well as in the number of tools available for its development. This has allowed significant progress and the creation of a completely new sector. There are many companies that turn to these new technologies in order to be able to process big amounts of data and obtain interesting and reliable results and outcomes from the analysis of these data. We also need to consider that hidden values exist within the data and only surface when processing the data on an appropriate manner and by using the adequate tools that will provide a sense to them and make possible the extraction of trustworthy results for further analysis. It is undeniable that the importance of the economy on people’s life is huge. Private capitals from the investors flow into the financial markets and different stock exchanges altering stock prices significantly depending on the mood and appetite of the investors due to other external factors such as economic news, rumours, decisions made by governmental institutions or central banks on the different regions, or simply the expectations on the market’s future reactions/movements, among others. All these also have then an impact on the real economy. From the need of analysing the data coming from these markets and by making the most out of the Big Data technology and its benefits, we will focus our end-of-degree study on the testing and implementation of new tools and technologies for analysis of Big Data (massive amount of data) and investment forecasting, with special focus on the financial services industry, that would help to extract accurate and reliable results for further analysis of the financial markets on an efficient, effective, fast, versatile and scalable way. In order to reach this goal, we will use during our project two main technologies used on the world of Big Data: Hadoop and Hive, who provide the required tools needed for the treatment and processing of big volumes of data. Once the project has been finalized, we will be able to extract information from the different financial markets and stock exchanges and load them into the Big Data system that has been design in order to process and analyse from the results extracted from the application of algorithmic trading. Furthermore, we will consider different scenarios and build alternative designs in order to adjust our infrastructure to the different objectives and requirements of the user, also in other fields aside of the financial markets, and suffice their needs.
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Big data, Proceso de datos, Arquitectura de redes, Proceso en paralelo
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