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Here is a Review of the Book "Real-time Big Data Analytics".

 

In the increasingly connected world, the number of data-generating sources is consistently on the rise. This trend and the transition have induced many distinct outcomes: the data size is exponentially growing, the data structure, scope, and speed is also evolving fast, etc. There are big, fast, streaming and IoT data emanating from disparate and distributed sources. There is a widespread realization that the data heaps implicitly possess a variety of actionable insights, which is indispensable for deftly and decisively steering any organization in the right direction. Therefore, there is a clarion call for unearthing a bevy of path-breaking techniques and tools for effectively ingesting, processing, and mining the massive volumes of data for squeezing out useful and usable intelligence. The pioneering Hadoop paradigm has brought in the real disruption on big data, which turns out to be the new normal.

 

In this context, the emergence of the highly deliberated and discoursed Hadoop technique is being widely applauded and adopted across. There are multiple Hadoop implementations in the marketplace these days. Both open source and commercial-grade software solutions are spitting out the data-driven insights and enabling insights-driven decisions for institutions, individuals, and innovators to be distinctively different in their deeds, decisions, and deals. Typically there are two key processing types: the batch and the real-time processing. Hadoop is primarily for doing batch processing of big data. However, the recent trends indicate the need for real-time processing of big data. No doubt, there are several challenges associated with the real-time analytics of tremendous amount of poly-structured data. There are value-added and venerable approaches and articulations in the form of platform-centric as well as infrastructure-specific solutions for efficiently tackling this emerging expectation.

 

In this book, the authors have clearly focused on hugely popular Apache Spark and Storm and other associated software solutions in order to expound all that are needed to empower big data architects and consultants, software engineers and developers with the right and relevant knowledge to build, deploy and deliver sophisticated real-time services and applications. This is a well-written book stuffed and sandwiched with a lot of practical examples, code snippets and easy-to-use optimization tips for equipping IT practitioners and professionals to jump into the data analytics domain quickly and easily.