Packt Publishing, 2018. — 312 p. — ISBN: 1783554398.
Big Data Analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to bring out hidden patterns and insights from the data which otherwise cannot be analyzed through traditional systems.
Through this book, you'll learn to setup big data environment on the AWS/Azure platform and configure various tools for performing analytical operations on big data table comprising of millions of records. Furthermore, you'll learn to explore various other components of hadoop ecosystem such as YARN, MapReduce, HDFS, HIVE, etc to perform various analytical operations. As you progress further, you'll be introduced to NoSQL databases for efficient querying and storage of data. To scale up processing time you'll learn to integrate Spark in to your environment and understand how its components - Spark Streaming, MLLib, etc can be used for quicker computations.
Once you have gained mastery over mining and organizing the data, you'll learn to derive ad interpret meaningful analysis of data using predictive, prescriptive, statistical and other form of machine learning techniques. You'll learn to implement various supervised, unsupervised and deep learning models with the help of real-world examples to gain detailed sense of understanding of machine learning is in practice. By the end of the book, you will have a very clear and concrete understanding of what Big Data Analytics means, what tools and techniques organizations are using to implement their Big Data platforms, how they are driving revenues and how users can develop their own solution based on the step-by-step approach articulated in the book.