Nowadays many experts qualify data as the new oil. Extracting real knowledge from huge data sets of raw data is a challenging activity and one of the most demanded jobs currently. When having high loads of numerical data stored as rows, the best way to understand the whole picture is by depicting the dataset in charts. In addition, one of the mission of economists is to translate the reality we live in to data so the situations can be analyzed, compared and studied. Household Consumption is one of the most important macroeconomic indexes because it represents the source of the economic activity of a country by its most important actor, families. By combining the coding skills required for developing a web application that can manage data and display it in charts and the knowledge related with Household Consumption’s determinants and the theory of consumption, useful conclusions can be extracted from a dataset. Without the named skills it would be impossible to extract any important idea because the quantity of information is massive. The final thesis of a degree is not only an assignment but the opportunity to learn something new and this thesis follows this principle. In the first part of the thesis, the development of the application is explained. The development has been divided in iterations and each iteration consists on a set of tasks to be done. It includes all the considerations and decisions that have been taken in order to make the most usable and useful application. This application has been done on top of another project called Rhizomer. Rhizomer is a faceted browser for exploring semantic data from SPARQL endpoints in an interactive manner it is maintained by Roberto García, one of the directors of this thesis. However, the system lacked of a usable way of exploring numerical data so the development of the application is focused on building a feature of Rhizomer that works as a chart visualizer. The second part focuses on the analysis of consumption from a theoretical point of view and then using empirical data from the European Union (EU). The goal of the part is to demonstrate the theoretical knowledge of consumption with the data from the European Union using the different features developed.