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Table Of Contents
Building Websites with VB.NET and DotNetNuke 4
When approaching a use case or an analysis, it is very important to understand how large the data we focus on is or will be in the future, as the dimension of the datasets may very well impact both the technologies we use and the analysis that we can do. As already mentioned, some of the approaches that have been developed on small datasets hardly scale to real-world applications and larger datasets, making them useless in practice.
When dealing with (possibly) large graphs, it is crucial to understand potential bottlenecks and limitation of the tools, technologies, and/or algorithms we use, assessing which part of our application/analysis may not scale when increasing the number of nodes or edges. Even more importantly, it is crucial to structure a data-driven application, however simple or at early proof of concept (POC) stages, in a way that would allow its scaling out in the future when data/users would increase, without rewriting the whole application...
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