| Sumario: | This is the perfect starting point for IT professionals and students interested in making sense of their organization's massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you'll develop the know-how you need to effectively interpret data. This book provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis; details different data visualization techniques that can be used to showcase and summarize your data; explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques; includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark. --
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