Carregant...
Tipus de document
Treball de fi de grauData de publicació
Llicència de publicació
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/59410
Processat i visualització d'entorns big data
Títol de la revista
Autors
Director/Tutor
ISSN de la revista
Títol del volum
Recurs relacionat
Resum
This project proposes the union of two concepts with a growing trend in the technology sector, such as Big Data and Business Intelligence, resulting in an interactive display to the user a set of public data.
Making worth of Big Data and Business Intelligence tools for large volumes of data such as Cloudera based on the Hadoop framework, implementation of MapReduce distributed programming paradigm, developed by Google, plays an important role for its scalability and ease to parallelize one software. In addition we also make use of Pentaho BI Suite is a set of free programs to generate business intelligence (BI), including integrated reporting tools. For this reason they are used in this project.
Starting from a large set of public data on Wikipedia about the searches performed daily, structured a traditional Business Intelligence architecture to treat, process and store the files mentioned above. This is the first part of the process.
The second part of the process consists of extracting information that have previously downloaded and stored through the dataset files in order to display the information in a way that the user can draw their own conclusions, ie, making reports.
Finally, the creation of dashboards that goes a step beyond the typical implementation of a display Business Intelligence, icomo are reporting.
To achieve this purpose we will use most of the tools that allow programs Pentaho BI Suite with all that important information.
Descripció
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2014, Director: Enric Biosca Trias
Citació
Citació
BLESA SIERRA, César. Processat i visualització d'entorns big data. [consulta: 25 de febrer de 2026]. [Disponible a: https://hdl.handle.net/2445/59410]