Building Big Data Applications

• Author : Krish Krishnan
• Publisher : Academic Press
• Release : 15 November 2019

Building Big Data Applications helps data managers and their organizations make the most of unstructured data with an existing data warehouse. It provides readers with what they need to know to make sense of how Big Data fits into the world of Data Warehousing. Readers will learn about infrastructure options and integration and come away with a solid understanding on how to leverage various architectures for integration. The book includes a wide range of use cases that will help data

• Author : Anonim
• Publisher : Unknown
• Release : 21 June 2021

• Author : Syed Muhammad Fahad Akhtar
• Publisher : Packt Publishing Ltd
• Release : 21 June 2018

A comprehensive end-to-end guide that gives hands-on practice in big data and Artificial Intelligence Key Features Learn to build and run a big data application with sample code Explore examples to implement activities that a big data architect performs Use Machine Learning and AI for structured and unstructured data Book Description The big data architects are the “masters” of data, and hold high value in today’s market. Handling big data, be it of good or bad quality, is not

• Author : Reza Arghandeh,Yuxun Zhou
• Publisher : Elsevier
• Release : 27 November 2017

Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement data in electricity transmission and distribution level. The book focuses on rapidly modernizing monitoring systems, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous

• Author : Venkat Ankam
• Publisher : Unknown
• Release : 26 August 2016

A handy reference guide for data analysts and data scientists to fetch "Value" out of big data analytics using Spark on Hadoop ClustersAbout This Book* Practical tutorial with real-world examples that explores Spark on Hadoop clusters* This book is based on the latest version of Apache Spark and Hadoop integrated with the most commonly used tools* Learn about all the Spark stack components including the latest topics such as DataFrames, DataSets, and SparkRWho This Book Is ForThough this book is

• Author : David Feinleib
• Publisher : Apress
• Release : 26 September 2014

Investors and technology gurus have called big data one of the most important trends to come along in decades. Big Data Bootcamp explains what big data is and how you can use it in your company to become one of tomorrow’s market leaders. Along the way, it explains the very latest technologies, companies, and advancements. Big data holds the keys to delivering better customer service, offering more attractive products, and unlocking innovation. That’s why, to remain competitive, every

• Author : Ivan Mistrik,Rami Bahsoon,Nour Ali,Maritta Heisel,Bruce Maxim
• Publisher : Morgan Kaufmann
• Release : 12 June 2017

Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied

• Author : Nataraj Dasgupta
• Publisher : Packt Publishing Ltd
• Release : 15 January 2018

Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to

• Author : Irfan Elahi
• Publisher : Apress
• Release : 29 August 2019

Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark. The book begins by introducing you to Scala and establishes a firm contextual understanding of why you should learn this language, how it stands in comparison to Java, and how Scala is related to Apache Spark for big data analytics. Next, you’ll set up the Scala environment ready for examining your first Scala programs. This is followed by sections

• Author : Marie Beaugureau
• Publisher : Unknown
• Release : 21 June 2021

With datasets growing increasingly large, the need for custom data solutions has soared as well. This Learning Path will take you through the entire process of designing and building data applications that can visualize, navigate, and interpret reams of data. Get a thorough introduction to the most important tools in the big data ecosystem.

• Author : Pradeep Pasupuleti,Beulah Salome Purra
• Publisher : Packt Publishing Ltd
• Release : 26 November 2015

Explore architectural approaches to building Data Lakes that ingest, index, manage, and analyze massive amounts of data using Big Data technologies About This Book Comprehend the intricacies of architecting a Data Lake and build a data strategy around your current data architecture Efficiently manage vast amounts of data and deliver it to multiple applications and systems with a high degree of performance and scalability Packed with industry best practices and use-case scenarios to get you up-and-running Who This Book Is

• Author : Jan Kunigk,Ian Buss,Paul Wilkinson,Lars George
• Publisher : O'Reilly Media
• Release : 05 December 2018

There’s a lot of information about big data technologies, but splicing these technologies into an end-to-end enterprise data platform is a daunting task not widely covered. With this practical book, you’ll learn how to build big data infrastructure both on-premises and in the cloud and successfully architect a modern data platform. Ideal for enterprise architects, IT managers, application architects, and data engineers, this book shows you how to overcome the many challenges that emerge during Hadoop projects. You’

• Author : Rajat Mehta
• Publisher : Packt Publishing Ltd
• Release : 31 July 2017

Learn the basics of analytics on big data using Java, machine learning and other big data tools About This Book Acquire real-world set of tools for building enterprise level data science applications Surpasses the barrier of other languages in data science and learn create useful object-oriented codes Extensive use of Java compliant big data tools like apache spark, Hadoop, etc. Who This Book Is For This book is for Java developers who are looking to perform data analysis in production

• Author : Dominik Ryzko
• Publisher : John Wiley & Sons
• Release : 31 March 2020

Provides an up-to-date analysis of big data and multi-agent systems The term Big Data refers to the cases, where data sets are too large or too complex for traditional data-processing software. With the spread of new concepts such as Edge Computing or the Internet of Things, production, processing and consumption of this data becomes more and more distributed. As a result, applications increasingly require multiple agents that can work together. A multi-agent system (MAS) is a self-organized computer system that

• Author : Hien Luu
• Publisher : Apress
• Release : 16 August 2018

Develop applications for the big data landscape with Spark and Hadoop. This book also explains the role of Spark in developing scalable machine learning and analytics applications with Cloud technologies. Beginning Apache Spark 2 gives you an introduction to Apache Spark and shows you how to work with it. Along the way, you’ll discover resilient distributed datasets (RDDs); use Spark SQL for structured data; and learn stream processing and build real-time applications with Spark Structured Streaming. Furthermore, you’ll learn