SQL Server Big Data Clusters

SQL Server Big Data Clusters
Author: Benjamin Weissman,Enrico van de Laar
Publsiher: Apress
Total Pages: 246
Release: 2019-11-26
ISBN: 1484251105
Category: Computers
Language: EN, FR, DE, ES & NL

SQL Server Big Data Clusters Book Excerpt:

Get a head-start on learning one of SQL Server 2019’s latest and most impactful features—Big Data Clusters—that combines large volumes of non-relational data for analysis along with data stored relationally inside a SQL Server database. This book provides a first look at Big Data Clusters based upon SQL Server 2019 Release Candidate 1. Start now and get a jump on your competition in learning this important new feature. Big Data Clusters is a feature set covering data virtualization, distributed computing, and relational databases and provides a complete AI platform across the entire cluster environment. This book shows you how to deploy, manage, and use Big Data Clusters. For example, you will learn how to combine data stored on the HDFS file system together with data stored inside the SQL Server instances that make up the Big Data Cluster. Filled with clear examples and use cases, this book provides everything necessary to get started working with Big Data Clusters in SQL Server 2019 using Release Candidate 1. You will learn about the architectural foundations that are made up from Kubernetes, Spark, HDFS, and SQL Server on Linux. You then are shown how to configure and deploy Big Data Clusters in on-premises environments or in the cloud. Next, you are taught about querying. You will learn to write queries in Transact-SQL—taking advantage of skills you have honed for years—and with those queries you will be able to examine and analyze data from a wide variety of sources such as Apache Spark. Through the theoretical foundation provided in this book and easy-to-follow example scripts and notebooks, you will be ready to use and unveil the full potential of SQL Server 2019: combining different types of data spread across widely disparate sources into a single view that is useful for business intelligence and machine learning analysis. What You Will LearnInstall, manage, and troubleshoot Big Data Clusters in cloud or on-premise environments Analyze large volumes of data directly from SQL Server and/or Apache Spark Manage data stored in HDFS from SQL Server as if it were relational data Implement advanced analytics solutions through machine learning and AI Expose different data sources as a single logical source using data virtualization Who This Book Is For For data engineers, data scientists, data architects, and database administrators who want to employ data virtualization and big data analytics in their environment

Noise Filtering for Big Data Analytics

Noise Filtering for Big Data Analytics
Author: Souvik Bhattacharyya,Koushik Ghosh
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 164
Release: 2022-06-21
ISBN: 3110697211
Category: Computers
Language: EN, FR, DE, ES & NL

Noise Filtering for Big Data Analytics Book Excerpt:

This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model. Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information. This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.

Big Data Analytics in Bioinformatics and Healthcare

Big Data Analytics in Bioinformatics and Healthcare
Author: Wang, Baoying
Publsiher: IGI Global
Total Pages: 528
Release: 2014-10-31
ISBN: 1466666129
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics in Bioinformatics and Healthcare Book Excerpt:

As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.

Introduction to Data Science and Machine Learning

Introduction to Data Science and Machine Learning
Author: Keshav Sud,Pakize Erdogmus,Seifedine Kadry
Publsiher: BoD – Books on Demand
Total Pages: 232
Release: 2020-03-25
ISBN: 1838803335
Category: Computers
Language: EN, FR, DE, ES & NL

Introduction to Data Science and Machine Learning Book Excerpt:

Introduction to Data Science and Machine Learning has been created with the goal to provide beginners seeking to learn about data science, data enthusiasts, and experienced data professionals with a deep understanding of data science application development using open-source programming from start to finish. This book is divided into four sections: the first section contains an introduction to the book, the second covers the field of data science, software development, and open-source based embedded hardware; the third section covers algorithms that are the decision engines for data science applications; and the final section brings together the concepts shared in the first three sections and provides several examples of data science applications.

Big Data Concepts Methodologies Tools and Applications

Big Data  Concepts  Methodologies  Tools  and Applications
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 2478
Release: 2016-04-20
ISBN: 1466698411
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Concepts Methodologies Tools and Applications Book Excerpt:

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.

Handbook of Research on Cloud Infrastructures for Big Data Analytics

Handbook of Research on Cloud Infrastructures for Big Data Analytics
Author: Raj, Pethuru
Publsiher: IGI Global
Total Pages: 570
Release: 2014-03-31
ISBN: 1466658657
Category: Computers
Language: EN, FR, DE, ES & NL

Handbook of Research on Cloud Infrastructures for Big Data Analytics Book Excerpt:

Clouds are being positioned as the next-generation consolidated, centralized, yet federated IT infrastructure for hosting all kinds of IT platforms and for deploying, maintaining, and managing a wider variety of personal, as well as professional applications and services. Handbook of Research on Cloud Infrastructures for Big Data Analytics focuses exclusively on the topic of cloud-sponsored big data analytics for creating flexible and futuristic organizations. This book helps researchers and practitioners, as well as business entrepreneurs, to make informed decisions and consider appropriate action to simplify and streamline the arduous journey towards smarter enterprises.

Big Data Analytics and Knowledge Discovery

Big Data Analytics and Knowledge Discovery
Author: Ladjel Bellatreche,Sharma Chakravarthy
Publsiher: Springer
Total Pages: 488
Release: 2017-08-11
ISBN: 3319642839
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Analytics and Knowledge Discovery Book Excerpt:

This book constitutes the refereed proceedings of the 19th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2017, held in Lyon, France, in August 2017. The 24 revised full papers and 11 short papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in the following topical sections: new generation data warehouses design; cloud and NoSQL databases; advanced programming paradigms; non-functional requirements satisfaction; machine learning; social media and twitter analysis; sentiment analysis and user influence; knowledge discovery; and data flow management and optimization.

Trends in Communication Cloud and Big Data

Trends in Communication  Cloud  and Big Data
Author: Hiren Kumar Deva Sarma,Bhaskar Bhuyan,Samarjeet Borah,Nitul Dutta
Publsiher: Springer Nature
Total Pages: 168
Release: 2020-01-02
ISBN: 9811516243
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Trends in Communication Cloud and Big Data Book Excerpt:

This book presents the outcomes of the Third National Conference on Communication, Cloud and Big Data (CCB) held on November 2–3, 2018, at Sikkim Manipal Institute of Technology, Majitar, Sikkim. Featuring a number of papers from the conference, it explores various aspects of communication, computation, cloud, and big data, including routing in cognitive radio wireless sensor networks, big data security issues, routing in ad hoc networks, routing protocol for Internet of things (IoT), and algorithm for imaging quality enhancement.

Big Data For Dummies

Big Data For Dummies
Author: Judith S. Hurwitz,Alan Nugent,Fern Halper,Marcia Kaufman
Publsiher: John Wiley & Sons
Total Pages: 336
Release: 2013-04-02
ISBN: 1118644174
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data For Dummies Book Excerpt:

Find the right big data solution for your business ororganization Big data management is one of the major challenges facingbusiness, industry, and not-for-profit organizations. Data setssuch as customer transactions for a mega-retailer, weather patternsmonitored by meteorologists, or social network activity can quicklyoutpace the capacity of traditional data management tools. If youneed to develop or manage big data solutions, you'll appreciate howthese four experts define, explain, and guide you through this newand often confusing concept. You'll learn what it is, why itmatters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importanceto businesses, not-for-profit organizations, government, and ITprofessionals Authors are experts in information management, big data, and avariety of solutions Explains big data in detail and discusses how to select andimplement a solution, security concerns to consider, data storageand presentation issues, analytics, and much more Provides essential information in a no-nonsense,easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helpsyou take charge of big data solutions for your organization.

Advances in Big Data

Advances in Big Data
Author: Plamen Angelov,Yannis Manolopoulos,Lazaros Iliadis,Asim Roy,Marley Vellasco
Publsiher: Springer
Total Pages: 348
Release: 2016-10-20
ISBN: 3319478982
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Advances in Big Data Book Excerpt:

The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23–25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.

Transforming Management with AI Big Data and IoT

Transforming Management with AI  Big Data  and IoT
Author: Fadi Al-Turjman,Satya Prakash Yadav,Manoj Kumar,Vibhash Yadav,Thompson Stephan
Publsiher: Springer Nature
Total Pages: 135
Release: 2022
ISBN: 3030867498
Category: Artificial intelligence
Language: EN, FR, DE, ES & NL

Transforming Management with AI Big Data and IoT Book Excerpt:

This book discusses the effect that artificial intelligence (AI) and Internet of Things (IoT) have on industry. The authors start by showing how the application of these technologies has already stretched across domains such as law, political science, policy, and economics and how it will soon permeate areas of autonomous transportation, education, and space exploration, only to name a few. The authors then discuss applications in a variety of industries. Throughout the volume, the authors provide detailed, well-illustrated treatments of each topic with abundant examples and exercises. This book provides relevant theoretical frameworks and the latest empirical research findings in various applications. The book is written for professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society, that is, trust at the level of the global economy, of networks and organizations, of teams and work groups, of information systems and, finally, trust at the level of individuals as actors in the networked environments. Presents research in various industries and how artificial intelligence and Internet of Things is changing the landscape of business and management; Includes new and innovative features in artificial intelligence and IoT that can help in raising economic efficiency at both micro and macro levels; Examines case studies with tried and tested approaches to resolution of typical problems in each application of study.

Networking for Big Data

Networking for Big Data
Author: Shui Yu,Xiaodong Lin,Jelena Misic,Xuemin (Sherman) Shen
Publsiher: CRC Press
Total Pages: 432
Release: 2015-07-28
ISBN: 1482263505
Category: Computers
Language: EN, FR, DE, ES & NL

Networking for Big Data Book Excerpt:

Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data. Starting with a comprehensive introduction to Big Data and its networking issues, it offers deep technical coverage of both theory and applications. The book is divided into four sections: introduction to Big Data, networking theory and design for Big Data, networking security for Big Data, and platforms and systems for Big Data applications. Focusing on key networking issues in Big Data, the book explains network design and implementation for Big Data. It examines how network topology impacts data collection and explores Big Data storage and resource management. Addresses the virtual machine placement problem Describes widespread network and information security technologies for Big Data Explores network configuration and flow scheduling for Big Data applications Presents a systematic set of techniques that optimize throughput and improve bandwidth for efficient Big Data transfer on the Internet Tackles the trade-off problem between energy efficiency and service resiliency The book covers distributed Big Data storage and retrieval as well as security, trust, and privacy protection for Big Data collection, storage, and search. It discusses the use of cloud infrastructures and highlights its benefits to overcome the identified issues and to provide new approaches for managing huge volumes of heterogeneous data. The text concludes by proposing an innovative user data profile-aware policy-based network management framework that can help you exploit and differentiate user data profiles to achieve better power efficiency and optimized resource management.

Internet of Things and Big Data Analytics Toward Next Generation Intelligence

Internet of Things and Big Data Analytics Toward Next Generation Intelligence
Author: Nilanjan Dey,Aboul Ella Hassanien,Chintan Bhatt,Amira S. Ashour,Suresh Chandra Satapathy
Publsiher: Springer
Total Pages: 549
Release: 2017-08-14
ISBN: 331960435X
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Internet of Things and Big Data Analytics Toward Next Generation Intelligence Book Excerpt:

This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.

High Performance Big Data Computing

High Performance Big Data Computing
Author: Dhabaleswar K. Panda,Xiaoyi Lu,Dipti Shankar
Publsiher: MIT Press
Total Pages: 272
Release: 2022-08-02
ISBN: 0262369427
Category: Computers
Language: EN, FR, DE, ES & NL

High Performance Big Data Computing Book Excerpt:

An in-depth overview of an emerging field that brings together high-performance computing, big data processing, and deep lLearning. Over the last decade, the exponential explosion of data known as big data has changed the way we understand and harness the power of data. The emerging field of high-performance big data computing, which brings together high-performance computing (HPC), big data processing, and deep learning, aims to meet the challenges posed by large-scale data processing. This book offers an in-depth overview of high-performance big data computing and the associated technical issues, approaches, and solutions. The book covers basic concepts and necessary background knowledge, including data processing frameworks, storage systems, and hardware capabilities; offers a detailed discussion of technical issues in accelerating big data computing in terms of computation, communication, memory and storage, codesign, workload characterization and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It presents a detailed discussion of big data computing systems and applications with high-performance networking, computing, and storage technologies, including state-of-the-art designs for data processing and storage systems. Finally, the book considers some advanced research topics in high-performance big data computing, including designing high-performance deep learning over big data (DLoBD) stacks and HPC cloud technologies.

Research Advances in the Integration of Big Data and Smart Computing

Research Advances in the Integration of Big Data and Smart Computing
Author: Mallick, Pradeep Kumar
Publsiher: IGI Global
Total Pages: 374
Release: 2015-10-13
ISBN: 146668738X
Category: Computers
Language: EN, FR, DE, ES & NL

Research Advances in the Integration of Big Data and Smart Computing Book Excerpt:

The volume, complexity, and irregularity of computational data in modern algorithms and simulations necessitates an unorthodox approach to computing. Understanding the facets and possibilities of soft computing algorithms is necessary for the accurate and timely processing of complex data. Research Advances in the Integration of Big Data and Smart Computing builds on the available literature in the realm of Big Data while providing further research opportunities in this dynamic field. This publication provides the resources necessary for technology developers, scientists, and policymakers to adopt and implement new paradigms in computational methods across the globe. The chapters in this publication advance the body of knowledge on soft computing techniques through topics such as transmission control protocol for mobile ad hoc networks, feature extraction, comparative analysis of filtering techniques, big data in economic policy, and advanced dimensionality reduction methods.

Smart Agricultural Services Using Deep Learning Big Data and IoT

Smart Agricultural Services Using Deep Learning  Big Data  and IoT
Author: Gupta, Amit Kumar,Goyal, Dinesh,Singh, Vijander,Sharma, Harish
Publsiher: IGI Global
Total Pages: 280
Release: 2020-10-30
ISBN: 1799850048
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Smart Agricultural Services Using Deep Learning Big Data and IoT Book Excerpt:

The agricultural sector can benefit immensely from developments in the field of smart farming. However, this research area focuses on providing specific fixes to particular situations and falls short on implementing data-driven frameworks that provide large-scale benefits to the industry as a whole. Using deep learning can bring immense data and improve our understanding of various earth sciences and improve farm services to yield better crop production and profit. Smart Agricultural Services Using Deep Learning, Big Data, and IoT is an essential publication that focuses on the application of deep learning to agriculture. While highlighting a broad range of topics including crop models, cybersecurity, and sustainable agriculture, this book is ideally designed for engineers, programmers, software developers, agriculturalists, farmers, policymakers, researchers, academicians, and students.

Big Data Processing Using Spark in Cloud

Big Data Processing Using Spark in Cloud
Author: Mamta Mittal,Valentina E. Balas,Lalit Mohan Goyal,Raghvendra Kumar
Publsiher: Springer
Total Pages: 264
Release: 2018-06-16
ISBN: 9811305501
Category: Computers
Language: EN, FR, DE, ES & NL

Big Data Processing Using Spark in Cloud Book Excerpt:

The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been overcome by Spark. The book mainly focuses on the in-depth architecture of Spark and our understanding of Spark RDDs and how RDD complements big data’s immutable nature, and solves it with lazy evaluation, cacheable and type inference. It also addresses advanced topics in Spark, starting with the basics of Scala and the core Spark framework, and exploring Spark data frames, machine learning using Mllib, graph analytics using Graph X and real-time processing with Apache Kafka, AWS Kenisis, and Azure Event Hub. It then goes on to investigate Spark using PySpark and R. Focusing on the current big data stack, the book examines the interaction with current big data tools, with Spark being the core processing layer for all types of data. The book is intended for data engineers and scientists working on massive datasets and big data technologies in the cloud. In addition to industry professionals, it is helpful for aspiring data processing professionals and students working in big data processing and cloud computing environments.

Large Scale and Big Data

Large Scale and Big Data
Author: Sherif Sakr,Mohamed Gaber
Publsiher: CRC Press
Total Pages: 636
Release: 2014-06-25
ISBN: 1466581514
Category: Computers
Language: EN, FR, DE, ES & NL

Large Scale and Big Data Book Excerpt:

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing t

Big Data in Complex Systems

Big Data in Complex Systems
Author: Aboul Ella Hassanien,Ahmad Taher Azar,Vaclav Snasael,Janusz Kacprzyk,Jemal H. Abawajy
Publsiher: Springer
Total Pages: 499
Release: 2015-01-02
ISBN: 331911056X
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Big Data in Complex Systems Book Excerpt:

This volume provides challenges and Opportunities with updated, in-depth material on the application of Big data to complex systems in order to find solutions for the challenges and problems facing big data sets applications. Much data today is not natively in structured format; for example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search. Therefore transforming such content into a structured format for later analysis is a major challenge. Data analysis, organization, retrieval, and modeling are other foundational challenges treated in this book. The material of this book will be useful for researchers and practitioners in the field of big data as well as advanced undergraduate and graduate students. Each of the 17 chapters in the book opens with a chapter abstract and key terms list. The chapters are organized along the lines of problem description, related works, and analysis of the results and comparisons are provided whenever feasible.

Social Big Data Analytics

Social Big Data Analytics
Author: Bilal Abu-Salih,Pornpit Wongthongtham,Dengya Zhu,Kit Yan Chan,Amit Rudra
Publsiher: Springer Nature
Total Pages: 218
Release: 2021-03-10
ISBN: 9813366524
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Social Big Data Analytics Book Excerpt:

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.