Real Time Analytics
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Real Time Analytics
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Author : Byron Ellis
language : en
Publisher: John Wiley & Sons
Release Date : 2014-06-23
Real Time Analytics written by Byron Ellis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-23 with Computers categories.
Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's "recipe" layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.
Real Time Analytics
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Author : Byron Ellis
language : en
Publisher: CreateSpace
Release Date : 2014-09-30
Real Time Analytics written by Byron Ellis and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-30 with Computers categories.
Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner. The book includes: A deep discussion of streaming data systems and architectures Instructions for analyzing, storing, and delivering streaming data Tips on aggregating data and working with sets Information on data warehousing options and techniques Real-Time Analytics includes in-depth case studies for website analytics, Big Data, visualizing streaming and mobile data, and mining and visualizing operational data flows. The book's "recipe" layout lets readers quickly learn and implement different techniques. All of the code examples presented in the book, along with their related data sets, are available on the companion website.
Practical Real Time Data Processing And Analytics
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Author : Shilpi Saxena
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-09-28
Practical Real Time Data Processing And Analytics written by Shilpi Saxena and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-28 with Computers categories.
A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to deploy the solutions in production environments in the best possible manner. Style and Approach In this practical guide to real-time analytics, each chapter begins with a basic high-level concept of the topic, followed by a practical, hands-on implementation of each concept, where you can see the working and execution of it. The book is written in a DIY style, with plenty of practical use cases, well-explained code examples, and relevant screenshots and diagrams.
Stream Processing Unleashed Real Time Analytics For The Modern Era
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Author : Mrs.V.Suganthi
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-08-27
Stream Processing Unleashed Real Time Analytics For The Modern Era written by Mrs.V.Suganthi and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-27 with Computers categories.
Mrs.V.Suganthi, Assistant Professor, Department of Computer Science, C.T.T.E College for Women, Chennai,Tamil Nadu, India. Mr.Z.Harith Ahamed, Assistant Professor, Department of Computer Science, Jamal Mohamed College (Autonomous), Tiruchirappalli, Tamil Nadu, India. Dr.T.Shiek Pareeth, Assistant Professor, Department of Mathematics, Jamal Mohamed College (Autonomous), Tiruchirappalli, Tamil Nadu, India. Mrs.P.Indumathi, Assistant Professor, Department of Computer Science with Data Analytics, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, India. Mrs.S.Nandhinieswari, Assistant Professor, Department of Computer Science, Sri Ramakrishna Arts and Science College For Women, Coimbatore, Tamil Nadu, India.
Real Time Analytics Techniques To Analyze And Visualize Streaming Data
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Author : Agustin Attebery
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-05-18
Real Time Analytics Techniques To Analyze And Visualize Streaming Data written by Agustin Attebery and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-18 with categories.
Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Agustin Attebery teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development, analytics, real-time visualization, and Big Data streaming and is uniquely qualified to help you explore this revolutionary field. Moving from a description of the overall analytic architecture of real-time analytics to using specific tools to obtain targeted results, Real-Time Analytics leverages open source and modern commercial tools to construct robust, efficient systems that can provide real-time analysis in a cost-effective manner.
Building Real Time Analytics Applications
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Author : Darin Briskman
language : en
Publisher:
Release Date : 2023
Building Real Time Analytics Applications written by Darin Briskman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Database management categories.
Every organization needs insight to succeed and excel, and the primary foundation for insights today is data—whether it's internal data from operational systems or external data from partners, vendors, and public sources. But how can you use this data to create and maintain analytics applications capable of gaining real insights in real time? In this report, Darin Briskman explains that leading organizations like Netflix, Walmart, and Confluent have found that while traditional analytics still have value, it's not enough. These companies and many others are now building real-time analytics that deliver insights continually, on demand, and at scale—complete with interactive drill-down data conversations, subsecond performance at scale, and always-on reliability.
The Global Impact Of Renewable Energy And Data Analytics
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Author : Kingsley Onyeagusi
language : en
Publisher: GRIN Verlag
Release Date : 2024-01-08
The Global Impact Of Renewable Energy And Data Analytics written by Kingsley Onyeagusi and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-08 with Science categories.
Academic Paper from the year 2023 in the subject Politics - Environmental Policy, , language: English, abstract: This article explores the critical role of renewable energy and intelligence systems in developing countries seeking to expand energy access and for developed nations working to decarbonise energy systems. The opportunities, challenges, and impacts of the renewable's revolution vary between poor nations with limited existing infrastructure and rich countries possessing advanced technical capabilities. However, data-driven solutions are invaluable in maximising clean energy potential everywhere while managing variability. By comparing and contrasting the nuances of integrating high shares of solar, wind, and other renewables onto grids in Asia, Africa, the Americas, and Europe, insights and best practices can be shared across borders. Artificial intelligence and machine learning are unlocking the promise of renewable energy worldwide through sophisticated forecasting of supply and demand, optimal location of projects, predictive maintenance of assets, and real-time management of complex systems. However, technology gaps and a lack of technical expertise hamper many developing nations. Targeted financing, capacity building, and knowledge transfer are critical to empowering these regions to benefit from data and renewables in providing affordable, reliable, and sustainable energy access. This article highlights significant trends, analyses case studies of success, and synthesises expert perspectives across the developed and developing world. By documenting the global impacts of renewables and analytics, stakeholders ranging from policymakers to investors can make informed decisions that steer all nations towards a decarbonised energy future that leaves no one behind. The insights can help guide an inclusive and just transition worldwide.
Dolap
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Author :
language : en
Publisher:
Release Date : 2005
Dolap written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Data warehousing categories.
Apache Kafka In Action
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Author : Anatoly Zelenin
language : en
Publisher: Simon and Schuster
Release Date : 2025-06-03
Apache Kafka In Action written by Anatoly Zelenin and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-03 with Computers categories.
Apache Kafka, start to finish. Apache Kafka in Action: From basics to production guides you through the concepts and skills you’ll need to deploy and administer Kafka for data pipelines, event-driven applications, and other systems that process data streams from multiple sources. Authors Anatoly Zelenin and Alexander Kropp have spent years using Kafka in real-world production environments. In this guide, they reveal their hard-won expert insights to help you avoid common Kafka pitfalls and challenges. Inside Apache Kafka in Action you’ll discover: • Apache Kafka from the ground up • Achieving reliability and performance • Troubleshooting Kafka systems • Operations, governance, and monitoring • Kafka use cases, patterns, and anti-patterns Clear, concise, and practical, Apache Kafka in Action is written for IT operators, software engineers, and IT architects working with Kafka every day. Chapter by chapter, it guides you through the skills you need to deliver and maintain reliable and fault-tolerant data-driven applications. Foreword by Adam Bellemare. About the technology Apache Kafka is the gold standard streaming data platform for real-time analytics, event sourcing, and stream processing. Acting as a central hub for distributed data, it enables seamless flow between producers and consumers via a publish-subscribe model. Kafka easily handles millions of events per second, and its rock-solid design ensures high fault tolerance and smooth scalability. About the book Apache Kafka in Action is a practical guide for IT professionals who are integrating Kafka into data-intensive applications and infrastructures. The book covers everything from Kafka fundamentals to advanced operations, with interesting visuals and real-world examples. Readers will learn to set up Kafka clusters, produce and consume messages, handle real-time streaming, and integrate Kafka into enterprise systems. This easy-to-follow book emphasizes building reliable Kafka applications and taking advantage of its distributed architecture for scalability and resilience. What's inside • Master Kafka’s distributed streaming capabilities • Implement real-time data solutions • Integrate Kafka into enterprise environments • Build and manage Kafka applications • Achieve fault tolerance and scalability About the reader For IT operators, software architects and developers. No experience with Kafka required. About the author Anatoly Zelenin is a Kafka expert known for workshops across Europe, especially in banking and manufacturing. Alexander Kropp specializes in Kafka and Kubernetes, contributing to cloud platform design and monitoring. Table of Contents Part 1 1 Introduction to Apache Kafka 2 First steps with Kafka Part 2 3 Exploring Kafka topics and messages 4 Kafka as a distributed log 5 Reliability 6 Performance Part 3 7 Cluster management 8 Producing and persisting messages 9 Consuming messages 10 Cleaning up messages Part 4 11 Integrating external systems with Kafka Connect 12 Stream processing 13 Governance 14 Kafka reference architecture 15 Kafka monitoring and alerting16 Disaster management 17 Comparison with other technologies 18 Kafka’s role in modern enterprise architectures Appendixes A Setting up a Kafka test environment B Monitoring setup
Big Data Machine And Deep Learning
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Author : Rajesh Kumar Mishra
language : en
Publisher: GRIN Verlag
Release Date : 2025-04-11
Big Data Machine And Deep Learning written by Rajesh Kumar Mishra and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-11 with Computers categories.
Scientific Study from the year 2025 in the subject Computer Sciences - Artificial Intelligence, , language: English, abstract: In recent times, developments in artificial intelligence (AI) and machine learning (ML) have propelled improvements in systems and control engineering. We exist in a time of extensive data, where AI and ML can evaluate large volumes of information instantly to enhance efficiency and precision in decisions based on data. In control engineering, for instance, AI algorithms can anticipate system behaviors and autonomously modify controls to enhance performance for better efficiency and dependability. ML models, with their ability to learn, consistently enhance their predictions and choices as they handle additional data, enabling systems to dynamically adjust to evolving environments and operational circumstances. This swift adjustment enhances the functions of current systems and enables the creation of groundbreaking solutions, like self-driving cars and intelligent power grids, which were previously deemed unfeasible. The rapid expansion of digital data has propelled significant advancements in Big Data analytics, Machine Learning, and Deep Learning. These technologies are increasingly integrated across industries, facilitating automated decision-making, predictive modeling, and advanced pattern recognition. This chapter provides an in-depth review of recent progress in these domains, emphasizing breakthroughs in scalable data processing frameworks, cloud and edge computing, AutoML, explainable AI, transformer architectures, self-supervised learning, and generative models. Furthermore, it explores key applications in healthcare, finance, and autonomous systems, along with challenges such as data privacy, ethical concerns, and computational constraints. The discussion concludes with future directions, highlighting the potential of federated learning, neuromorphic computing, and novel algorithmic improvements to further expand AI's impact across disciplines.