Leverage Opensource and Enterprise tools with best practices of implementing an analytical Big data solution from industry expert.
About This Book
* A perfect companion to boost your skills and apply techniques to store, process and analyse data for informed business decisions.
*Choose the best of the tools such as Hadoop, R, Python, Spark, NoSQL platforms to do Massive online Analysis.
*Follow an experts footsteps to learn statistical inference, machine learning, mathematical modelling and data visualisation.
Who This Book Is For
The book is intended for data scientists, big data engineer's , and analytical professionals who like to grow a demanding career in data architecture, analytics and governance .
As such, no prior knowledge in the field of Big Data is assumed, but the reader should be familiar with general concepts of information technology.
What You Will Learn
* Understand the (Real) meaning of Big Data Analytics and how it can help you in transforming your organization
*Provide a concrete framework of formulating a custom winning Big Data strategy for the enterprise
*Discuss industry-wide trends from real-world deployments of Big Data platforms across the industry
*Discuss how C-Level management in large global organisations are approaching their Big Data strategy
*Provide hands-on examples in various sections for more seasoned software professionals
*Simple lucid explanations to demystify confusing terms commonly used in Big Data Analytics & Data Science
*Provide step-by-step explanation of various Big Data topics in a chronological order but each chapter can also be read independently due to the modular organization of the chapters
*Develop, lead and put together a cost-effective yet robust enterprise-wide Analytics platform
*Going beyond general-purpose analytics to develop high-performance cutting edge analytic capabilities
In Detail
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.
