Introduction

This work attempts to create a framework for making good architectural decisions when faced with data challenges. A systematic way of approaching Big Data complex projects.

The document follows an architectural blueprint in order to classify the correct components in the Big Data architecture landscape. We can think in this blueprint as a way of standardize the names and roles of the different technologies used in an end-to-end Big Data project.

When Big Data projects reach a certain point, the should be agile and adaptable systems that can be easily modified, that requires to have a fair understanding of the software stack as a whole. This work try to help in the decision of which components to use thinking in his own areas of focus.

Many of the ideas, classifications and descriptions are based on other authors. I’ve paraphrased many of the sentences or entire paragraphs, because of I have not found a better way to express the ideas. At the end of this document I’ve posted the references per author.

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