Our documentation will introduce you to Mango Graph Studio, an environment for integrating, exploring, and analyzing heterogeneous networks. Mango began it's development in Summer 2014 as a response to a need for scalable and flexible methods for integrating massive data networks. Below you can find the mango documentation in the form of a PDF, ePub, or Mobi download, or you can read the entire document on GitBook.

Our Goals with Mango Graph Studio

Complex means "composed of many different parts". What word describes better the state of data analysis today? From open digital repositories to self reported personal information, companies and individuals have access to a treasure trove of information. But transforming this seemingly endless supply of data into practical applications continues to be a monolithic and many-headed beast. The analysis of data is defined as the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. This explosion of publicly available data means anyone can become a professional analyst. The major hurdle is time and complexity. Analysts often go through a multi-step process to download, clean, integrate, and analyze data. Time and effort is needed to logically organize the data before data exploration can begin. We hoped to develop a tool that enabled data analysts to interact with the data in a way that is effective, fast, and user-friendly. Mango grew out of the belief that complex does not have to mean difficult and overwhelming. Using a set of starting principles, complexity can be managed, integrated, and interpreted. We wanted to make serendipitous discoveries more accessible and user friendly. From this goal, we developed the Mango system and this book will introduce you, the reader, to the playground of network analysis.

As always, you can find the newest version of Mango by clicking here.

Complex Computation LLC team