标签:Big Data

Processing Big Data with Azure HDInsight 封面

Processing Big Data with Azure HDInsight

作者:Vinit Yadav

Get a jump start on using Azure HDInsight and Hadoop Ecosystem components. As most Hadoop and Big Data projects are written in either Java, Scala, or Python, this book minimizes the effort to learn another language and is written from the perspective of a .NET developer. Hadoop components are covered, including Hive, Pig, HBase, Storm, and Spark on Azure HDInsight, and code samples are written in .NET only. Processing Big Data with Azure HDInsight covers the fundamentals of big data, how busi

Tabular Modeling with SQL Server 2016 Analysis Services Cookbook 封面

Tabular Modeling with SQL Server 2016 Analysis Services Cookbook

作者:Derek Wilson

Key Features Build and deploy Tabular Model projects from relational data sources Leverage DAX and create high-performing calculated fields and measures Create ad-hoc reports based on a Tabular Model solution Useful tips to monitor and optimize your tabular solutions Book Description SQL Server Analysis Service (SSAS) has been widely used across multiple businesses to build smart online analytical reporting solutions. It includes two different types of modeling for analysis services: Tabular and

Handbook of Big Data Technologies 封面

Handbook of Big Data Technologies

作者:Albert Y. Zomaya, Sherif Sakr

This handbook offers comprehensive coverage of recent advancements in Big Data technologies and related paradigms.  Chapters are authored by international leading experts in the field, and have been reviewed and revised for maximum reader value. The volume consists of twenty-five chapters organized into four main parts. Part one covers the fundamental concepts of Big Data technologies including data curation mechanisms, data models, storage models, programming models and programming platforms. I

Internet of Things and Big Data Technologies for Next Generation Healthcare 封面

Internet of Things and Big Data Technologies for Next Generation Healthcare

作者:Amira S. Ashour, Chintan Bhatt, Nilanjan Dey

This comprehensive book focuses on better big-data security for healthcare organizations. Following an extensive introduction to the Internet of Things (IoT) in healthcare including challenging topics and scenarios, it offers an in-depth analysis of medical body area networks with the 5th generation of IoT communication technology along with its nanotechnology. It also describes a novel strategic framework and computationally intelligent model to measure possible security vulnerabilities in the

Pro Hadoop Data Analytics 封面

Pro Hadoop Data Analytics

作者:Kerry Koitzsch

Learn advanced analytical techniques and leverage existing toolkits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems which go beyond the basics of classification, clustering, and recommendation. In Pro Hadoop Data Analytics best practices are emphasized to ensure coherent, efficient development. A complete example system will be developed using s

Ethical Reasoning in Big Data 封面

Ethical Reasoning in Big Data

作者:Jeff Collmann, Sorin Adam Matei

This book springs from a multidisciplinary, multi-organizational, and multi-sector conversation about the privacy and ethical implications of research in human affairs using big data. The need to cultivate and enlist the public’s trust in the abilities of particular scientists and scientific institutions constitutes one of this book’s major themes. The advent of the Internet, the mass digitization of research information, and social media brought about, among many other things, the ability to ha

Big Data Fundamentals 封面

Big Data Fundamentals

作者:Paul Buhler, Thomas Erl, Wajid Khattak

The Definitive Plain-English Guide to Big Data for Business and Technology Professionals Big Data Fundamentals provides a pragmatic, no-nonsense introduction to Big Data. Best-selling IT author Thomas Erl and his team clearly explain key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. All coverage is supported with case study examples and numerous simple diagrams. The authors begin by explaining how Big Data can propel an organization forward by sol

SQL on Big Data 封面

SQL on Big Data

作者:SUMIT PAL

Learn various commercial and open source products that perform SQL on Big Data platforms. You will understand the architectures of the various SQL engines being used and how the tools work internally in terms of execution, data movement, latency, scalability, performance, and system requirements. This book consolidates in one place solutions to the challenges associated with the requirements of speed, scalability, and the variety of operations needed for data integration and SQL operations. Afte

Cloud Networking for Big Data 封面

Cloud Networking for Big Data

作者:Deze Zeng, Lin Gu, Song Guo

This book introduces two basic big data processing paradigms for batch data and streaming data. Representative programming frameworks are also presented, as well as software defined networking (SDN) and network function virtualization (NFV) technologies as key cloud networking technologies. The authors illustrate that SDN and NFV can be applied to benefit the big data processing by proposing a cloud networking framework. Based on the framework, two case studies examine how to improve the cost ef

Big Data Analysis 封面

Big Data Analysis

作者:Jerzy Stefanowski, Nathalie Japkowicz

This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks,

Big Data SMACK 封面

Big Data SMACK

作者:Isaac Ruiz, Raul Estrada

This book is about how to integrate full-stack open source big data architecture and how to choose the correct technology―Scala/Spark, Mesos, Akka, Cassandra, and Kafka―in every layer. Big data architecture is becoming a requirement for many different enterprises. So far, however, the focus has largely been on collecting, aggregating, and crunching large datasets in a timely manner. In many cases now, organizations need more than one paradigm to perform efficient analyses. Big Data SMACK explain

Apache Oozie Essentials 封面

Apache Oozie Essentials

作者:Jagat Jasjit Singh

As more and more organizations are discovering the use of big data analytics, interest in platforms that provide storage, computation, and analytic capabilities is booming exponentially. This calls for data management. Hadoop caters to this need. Oozie fulfils this necessity for a scheduler for a Hadoop job by acting as a cron to better analyze data. Apache Oozie Essentials starts off with the basics right from installing and configuring Oozie from source code on your Hadoop cluster to managing

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