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Curse of Dimensionality:
One of the most commonly faced problems while dealing with data analytics problem such as recommendation engines, text analytics is high-dimensional and sparse data. At many times, we face a situation where we have a large set of features and fewer data points, or we have data with very high feature vectors. In such scenarios, fitting a model to the dataset, results in lower predictive power of the model. This scenario is often termed as…Continue
Added by suresh kumar gorakala on February 28, 2016 at 9:30pm — No Comments
In our last blog we saw the key benefits of Data Lake, but let’s deep dive in to the internals of a Data Lake via discussing the key considerations and compositions.
Take in any solution considerations it is practical difficult to arrives with a one-size-fit-all architecture; hence it applies for a Data Lake too. Hence the Data Lake architecture considerations…Continue
Added by Kumar Chinnakali on February 13, 2016 at 10:42am — No Comments