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Proceedings of the XVII International symposium Symorg 2020

Proceedings of the XVII International symposium Symorg 2020
Author: Dušan Starčević
Publisher: FON
Total Pages: 751
Release: 2020-06-30
Genre: Business & Economics
ISBN: 8676803854

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Ever since 1989, the Faculty of Organizational Sciences, University of Belgrade, has been the host of SymOrg, an event that promotes scientific disciplines of organizing and managing a business. Traditionally, the Symposium has been an opportunity for its participants to share and exchange both academic and practical knowledge and experience in a pleasant and creative atmosphere. This time, however, due the challenging situation regarding the COVID-19 pandemic, we have decided that all the essential activities planned for the International Symposium SymOrg 2020 should be carried out online between the 7th and the 9th of September 2020. We are very pleased that the topic of SymOrg 2020, “Business and Artificial Intelligence”, attracted researchers from different institutions, both in Serbia and abroad. Why is artificial intelligence a disruptive technology? Simply because “it significantly alters the way consumers, industries, or businesses operate.” According to the European Commission document titled Artificial Intelligence for Europe 2018, AI is a key disruptive technology that has just begun to reshape the world. The Government of the Republic of Serbia has also recognized the importance of AI for the further development of its economy and society and has prepared an AI Development Strategy for the period between 2020 and 2025. The first step has already been made: the Science Fund of the Republic of Serbia, after a public call, has selected and financed twelve AI projects. This year, more than 200 scholars and practitioners authored and co-authored the 94 scientific and research papers that had been accepted for publication in the Proceedings. All the contributions to the Proceedings are classified into the following 11 sections: Information Systems and Technologies in the Era of Digital Transformation Smart Business Models and Processes Entrepreneurship, Innovation and Sustainable Development Smart Environment for Marketing and Communications Digital Human Resource Management Smart E-Business Quality 4.0 and International Standards Application of Artificial Intelligence in Project Management Digital and Lean Operations Management Transformation of Financial Services Methods and Applications of Data Science in Business and Society We are very grateful to our distinguished keynote speakers: Prof. Moshe Vardi, Rice University, USA, Prof. Blaž Zupan, University of Ljubljana, Slovenia, Prof. Vladan Devedžić, University of Belgrade, Serbia, Milica Đurić-Jovičić, PhD, Director, Science Fund of the Republic of Serbia, and Harri Ketamo, PhD, Founder & Chairman of HeadAI ltd., Finland. Also, special thanks to Prof. Dragan Vukmirović, University of Belgrade, Serbia and Prof. Zoran Ševarac, University of Belgrade, Serbia for organizing workshops in fields of Data Science and Machine Learning and to Prof. Rade Matić, Belgrade Business and Arts Academy of Applied Studies and Milan Dobrota, PhD, CEO at Agremo, Serbia, for their valuable contribution in presenting Serbian experiences in the field of AI. The Faculty of Organizational Sciences would to express its gratitude to the Ministry of Education, Science and Technological Development and all the individuals who have supported and contributed to the organization of the Symposium. We are particularly grateful to the contributors and reviewers who made this issue possible. But above all, we are especially thankful to the authors and presenters for making the SymOrg 2020 a success!


Load Balance For Distributed Real-time Computing Systems

Load Balance For Distributed Real-time Computing Systems
Author: Junhua Fang
Publisher: World Scientific
Total Pages: 259
Release: 2020-05-19
Genre: Computers
ISBN: 9811216169

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This illustrative compendium analyzes the load balancing problem in distributed stream processing systems and explores a set of high-performance real-time processing scheme based on key-based balancing strategy, join-matrix model and fault tolerance mechanisms.The volume succinctly provides the theoretical support for the proposed techniques. Through a rich set of experiments and comparisons with the other state-of-the-art techniques using both standard benchmarks and real data sets, the book comprehensively verifies the correctness and effectiveness of the proposed methods.This unique title is an excellent reference text for researchers in the fields of distributed stream processing, parallel system, cloud computing, etc.


Foundations of Scalable Systems

Foundations of Scalable Systems
Author: Ian Gorton
Publisher: "O'Reilly Media, Inc."
Total Pages: 339
Release: 2022-06-30
Genre: Computers
ISBN: 1098106016

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In many systems, scalability becomes the primary driver as the user base grows. Attractive features and high utility breed success, which brings more requests to handle and more data to manage. But organizations reach a tipping point when design decisions that made sense under light loads suddenly become technical debt. This practical book covers design approaches and technologies that make it possible to scale an application quickly and cost-effectively. Author Ian Gorton takes software architects and developers through the foundational principles of distributed systems. You'll explore the essential ingredients of scalable solutions, including replication, state management, load balancing, and caching. Specific chapters focus on the implications of scalability for databases, microservices, and event-based streaming systems. You will focus on: Foundations of scalable systems: Learn basic design principles of scalability, its costs, and architectural tradeoffs Designing scalable services: Dive into service design, caching, asynchronous messaging, serverless processing, and microservices Designing scalable data systems: Learn data system fundamentals, NoSQL databases, and eventual consistency versus strong consistency Designing scalable streaming systems: Explore stream processing systems and scalable event-driven processing


Hadoop Application Architectures

Hadoop Application Architectures
Author: Mark Grover
Publisher: "O'Reilly Media, Inc."
Total Pages: 425
Release: 2015-06-30
Genre: Computers
ISBN: 1491900059

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Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case. To reinforce those lessons, the book’s second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether you’re designing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process. This book covers: Factors to consider when using Hadoop to store and model data Best practices for moving data in and out of the system Data processing frameworks, including MapReduce, Spark, and Hive Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics Giraph, GraphX, and other tools for large graph processing on Hadoop Using workflow orchestration and scheduling tools such as Apache Oozie Near-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache Flume Architecture examples for clickstream analysis, fraud detection, and data warehousing


Data Management at Scale

Data Management at Scale
Author: Piethein Strengholt
Publisher: "O'Reilly Media, Inc."
Total Pages: 404
Release: 2020-07-29
Genre: Computers
ISBN: 1492054739

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As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata


Parallel Computing Architectures and APIs

Parallel Computing Architectures and APIs
Author: Vivek Kale
Publisher: CRC Press
Total Pages: 330
Release: 2019-12-06
Genre: Computers
ISBN: 1351029207

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Parallel Computing Architectures and APIs: IoT Big Data Stream Processing commences from the point high-performance uniprocessors were becoming increasingly complex, expensive, and power-hungry. A basic trade-off exists between the use of one or a small number of such complex processors, at one extreme, and a moderate to very large number of simpler processors, at the other. When combined with a high-bandwidth, interprocessor communication facility leads to significant simplification of the design process. However, two major roadblocks prevent the widespread adoption of such moderately to massively parallel architectures: the interprocessor communication bottleneck, and the difficulty and high cost of algorithm/software development. One of the most important reasons for studying parallel computing architectures is to learn how to extract the best performance from parallel systems. Specifically, you must understand its architectures so that you will be able to exploit those architectures during programming via the standardized APIs. This book would be useful for analysts, designers and developers of high-throughput computing systems essential for big data stream processing emanating from IoT-driven cyber-physical systems (CPS). This pragmatic book: Devolves uniprocessors in terms of a ladder of abstractions to ascertain (say) performance characteristics at a particular level of abstraction Explains limitations of uniprocessor high performance because of Moore’s Law Introduces basics of processors, networks and distributed systems Explains characteristics of parallel systems, parallel computing models and parallel algorithms Explains the three primary categorical representatives of parallel computing architectures, namely, shared memory, message passing and stream processing Introduces the three primary categorical representatives of parallel programming APIs, namely, OpenMP, MPI and CUDA Provides an overview of Internet of Things (IoT), wireless sensor networks (WSN), sensor data processing, Big Data and stream processing Provides introduction to 5G communications, Edge and Fog computing Parallel Computing Architectures and APIs: IoT Big Data Stream Processing discusses stream processing that enables the gathering, processing and analysis of high-volume, heterogeneous, continuous Internet of Things (IoT) big data streams, to extract insights and actionable results in real time. Application domains requiring data stream management include military, homeland security, sensor networks, financial applications, network management, web site performance tracking, real-time credit card fraud detection, etc.


Delta Lake: Up and Running

Delta Lake: Up and Running
Author: Bennie Haelen
Publisher: "O'Reilly Media, Inc."
Total Pages: 267
Release: 2023-10-16
Genre: Computers
ISBN: 1098139690

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With the surge in big data and AI, organizations can rapidly create data products. However, the effectiveness of their analytics and machine learning models depends on the data's quality. Delta Lake's open source format offers a robust lakehouse framework over platforms like Amazon S3, ADLS, and GCS. This practical book shows data engineers, data scientists, and data analysts how to get Delta Lake and its features up and running. The ultimate goal of building data pipelines and applications is to gain insights from data. You'll understand how your storage solution choice determines the robustness and performance of the data pipeline, from raw data to insights. You'll learn how to: Use modern data management and data engineering techniques Understand how ACID transactions bring reliability to data lakes at scale Run streaming and batch jobs against your data lake concurrently Execute update, delete, and merge commands against your data lake Use time travel to roll back and examine previous data versions Build a streaming data quality pipeline following the medallion architecture


Real-Time Streaming with Apache Kafka, Spark, and Storm

Real-Time Streaming with Apache Kafka, Spark, and Storm
Author: Brindha Priyadarshini Jeyaraman
Publisher: BPB Publications
Total Pages: 196
Release: 2021-08-20
Genre: Computers
ISBN: 9390684595

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Build a platform using Apache Kafka, Spark, and Storm to generate real-time data insights and view them through Dashboards. KEY FEATURES ● Extensive practical demonstration of Apache Kafka concepts, including producer and consumer examples. ● Includes graphical examples and explanations of implementing Kafka Producer and Kafka Consumer commands and methods. ● Covers integration and implementation of Spark-Kafka and Kafka-Storm architectures. DESCRIPTION Real-Time Streaming with Apache Kafka, Spark, and Storm is a book that provides an overview of the real-time streaming concepts and architectures of Apache Kafka, Storm, and Spark. The readers will learn how to build systems that can process data streams in real time using these technologies. They will be able to process a large amount of real-time data and perform analytics or generate insights as a result of this. The architecture of Kafka and its various components are described in detail. A Kafka Cluster installation and configuration will be demonstrated. The Kafka publisher-subscriber system will be implemented in the Eclipse IDE using the Command Line and Java. The book discusses the architecture of Apache Storm, the concepts of Spout and Bolt, as well as their applications in a Transaction Alert System. It also describes Spark's core concepts, applications, and the use of Spark to implement a microservice. To learn about the process of integrating Kafka and Storm, two approaches to Spark and Kafka integration will be discussed. This book will assist a software engineer to transition to a Big Data engineer and Big Data architect by providing knowledge of big data processing and the architectures of Kafka, Storm, and Spark Streaming. WHAT YOU WILL LEARN ● Creation of Kafka producers, consumers, and brokers using command line. ● End-to-end implementation of Kafka messaging system with Java in Eclipse. ● Perform installation and creation of a Storm Cluster and execute Storm Management commands. ● Implement Spouts, Bolts and a Topology in Storm for Transaction alert application system. ● Perform the implementation of a microservice using Spark in Scala IDE. ● Learn about the various approaches of integrating Kafka and Spark. ● Perform integration of Kafka and Storm using Java in the Eclipse IDE. WHO THIS BOOK IS FOR This book is intended for Software Developers, Data Scientists, and Big Data Architects who want to build software systems to process data streams in real time. To understand the concepts in this book, knowledge of any programming language such as Java, Python, etc. is needed. TABLE OF CONTENTS 1. Introduction to Kafka 2. Installing Kafka 3. Kafka Messaging 4. Kafka Producers 5. Kafka Consumers 6. Introduction to Storm 7. Installation and Configuration 8. Spouts and Bolts 9. Introduction to Spark 10. Spark Streaming 11. Kafka Integration with Storm 12. Kafka Integration with Spark