Zeppelin For Interactive Data Analytics

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Zeppelin For Interactive Data Analytics

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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-08

Zeppelin For Interactive Data Analytics written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-08 with Computers categories.

"Zeppelin for Interactive Data Analytics" "Zeppelin for Interactive Data Analytics" is the definitive guide for professionals and organizations seeking to harness the full potential of interactive analytics within modern data-driven environments. This comprehensive volume charts the evolution of data science notebooks, with in-depth explorations of architectures ranging from batch to real-time systems and a thorough analysis of Zeppelin's unique place in this landscape. Readers will gain a clear understanding of the critical use cases where immediacy and collaboration in analytics make a profound impact, while addressing the essential foundations of scalability, security, and governance that are crucial for today's enterprise deployments. At the heart of the book lies a detailed technical journey through Zeppelin's architecture, multi-language interpreter system, and the mechanics of storage, collaboration, and extension. Advanced topics illuminate best practices for interpreter customization, distributed and multi-tenant execution, resource isolation, and seamless integration with both structured and unstructured data sources. Attention is given to robust data governance, lineage, compliance, and metadata management, providing readers with actionable guidance for managing data flow in regulated environments. The book's practical focus extends to automating workflows, orchestrating notebook executions via APIs and schedulers, and embedding Zeppelin solutions into CI/CD pipelines for robust operationalization. The narrative is rounded out with sections on interactive visual analytics, machine learning integration, and innovations shaping the future of collaborative analytics. Users will benefit from hands-on strategies for building dynamic dashboards, developing polyglot analytics workflows, and leveraging state-of-the-art ML frameworks within Zeppelin. The final chapters address enterprise-grade concerns—role-based access, monitoring, disaster recovery, and future-proofing deployments— before exploring cutting-edge topics such as serverless execution, federated analytics, and emerging paradigms in user experience. Whether you are a data engineer, analytics architect, or technical decision-maker, this book equips you with the knowledge and best practices to deploy, operate, and innovate with Zeppelin at any scale.

Data Analytics Using Open Source Tools

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Author : Jeffrey Strickland
language : en
Publisher: Lulu.com
Release Date : 2016-07-20

Data Analytics Using Open Source Tools written by Jeffrey Strickland and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-20 with Business & Economics categories.

This book is about using open-source tools in data analytics. The book covers several subjects, including descriptive and predictive modeling, gradient boosting, cluster modeling, logistic regression, and artificial neural networks, among other topics.

Big Data And Analytics

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Author : Dr. Jugnesh Kumar
language : en
Publisher: BPB Publications
Release Date : 2024-03-05

Big Data And Analytics written by Dr. Jugnesh Kumar and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-05 with Computers categories.

Unveiling insights, unleashing potential: Navigating the depths of big data and analytics for a data-driven tomorrow KEY FEATURES ● Learn about big data and how it helps businesses innovate, grow, and make decisions efficiently. ● Learn about data collection, storage, processing, and analysis, along with tools and methods. ● Discover real-life examples of big data applications across industries, addressing challenges like privacy and security. DESCRIPTION Big data and analytics is an indispensable guide that navigates the complex data management and analysis. This comprehensive book covers the core principles, processes, and tools, ensuring readers grasp the essentials and progress to advanced applications. It will help you understand the different analysis types like descriptive, predictive, and prescriptive. Learn about NoSQL databases and their benefits over SQL. The book centers on Hadoop, explaining its features, versions, and main components like HDFS (storage) and MapReduce (processing). Explore MapReduce and YARN for efficient data processing. Gain insights into MongoDB and Hive, popular tools in the big data landscape. WHAT YOU WILL LEARN ● Grasp big data fundamentals and applications. ● Master descriptive, predictive, and prescriptive analytics. ● Understand HDFS, MapReduce, YARN, and their functionalities. ● Explore data storage, retrieval, and manipulation in a NoSQL database. ● Gain practical insights and apply them to real-world scenarios. WHO THIS BOOK IS FOR This book caters to a diverse audience, including data professionals, analysts, IT managers, and business intelligence practitioners. TABLE OF CONTENTS 1. Introduction to Big Data 2. Big Data Analytics 3. Introduction of NoSQL 4. Introduction to Hadoop 5. Map Reduce 6. Introduction to MongoDB

Scala And Spark For Big Data Analytics

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Author : Md. Rezaul Karim
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-07-25

Scala And Spark For Big Data Analytics written by Md. Rezaul Karim 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 2017-07-25 with Computers categories.

Harness the power of Scala to program Spark and analyze tonnes of data in the blink of an eye! About This Book Learn Scala's sophisticated type system that combines Functional Programming and object-oriented concepts Work on a wide array of applications, from simple batch jobs to stream processing and machine learning Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark Who This Book Is For Anyone who wishes to learn how to perform data analysis by harnessing the power of Spark will find this book extremely useful. No knowledge of Spark or Scala is assumed, although prior programming experience (especially with other JVM languages) will be useful to pick up concepts quicker. What You Will Learn Understand object-oriented & functional programming concepts of Scala In-depth understanding of Scala collection APIs Work with RDD and DataFrame to learn Spark's core abstractions Analysing structured and unstructured data using SparkSQL and GraphX Scalable and fault-tolerant streaming application development using Spark structured streaming Learn machine-learning best practices for classification, regression, dimensionality reduction, and recommendation system to build predictive models with widely used algorithms in Spark MLlib & ML Build clustering models to cluster a vast amount of data Understand tuning, debugging, and monitoring Spark applications Deploy Spark applications on real clusters in Standalone, Mesos, and YARN In Detail Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big. Style and approach Filled with practical examples and use cases, this book will hot only help you get up and running with Spark, but will also take you farther down the road to becoming a data scientist.

Apache Spark Unleashed Advanced Techniques For Data Processing And Analysis

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Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-14

Apache Spark Unleashed Advanced Techniques For Data Processing And Analysis written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-14 with Computers categories.

"Apache Spark Unleashed: Advanced Techniques for Data Processing and Analysis" delves into the sophisticated realm of Apache Spark, crafted for professionals eager to amplify their expertise in managing complex data processing challenges. This extensive guide traverses the Spark ecosystem, starting from essential components like RDDs and DataFrames, extending to cutting-edge subjects such as real-time data handling with Spark Structured Streaming and advanced predictive modeling with Spark MLlib. The book is meticulously organized to lead readers through Apache Spark’s architecture, setup and configuration, comprehensive data processing techniques, structured data querying, performance tuning, deployment strategies, and monitoring aspects. Each chapter is enriched with practical examples, insightful case studies, and industry best practices, ensuring that readers grasp both the theoretical foundations and their practical applications in real-world environments. Whether you are a software engineer, data scientist, data engineer, or analyst, "Apache Spark Unleashed: Advanced Techniques for Data Processing and Analysis" stands as a vital resource to effectively harness Apache Spark's capabilities, optimize your data processing operations, and realize scalable, high-performance data analytics solutions. This is your invitation to master Apache Spark and elevate your data processing proficiency to unparalleled heights.

Apache Spark Machine Learning Blueprints

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Author : Alex Liu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-05-30

Apache Spark Machine Learning Blueprints written by Alex Liu 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 2016-05-30 with Computers categories.

Develop a range of cutting-edge machine learning projects with Apache Spark using this actionable guide About This Book Customize Apache Spark and R to fit your analytical needs in customer research, fraud detection, risk analytics, and recommendation engine development Develop a set of practical Machine Learning applications that can be implemented in real-life projects A comprehensive, project-based guide to improve and refine your predictive models for practical implementation Who This Book Is For If you are a data scientist, a data analyst, or an R and SPSS user with a good understanding of machine learning concepts, algorithms, and techniques, then this is the book for you. Some basic understanding of Spark and its core elements and application is required. What You Will Learn Set up Apache Spark for machine learning and discover its impressive processing power Combine Spark and R to unlock detailed business insights essential for decision making Build machine learning systems with Spark that can detect fraud and analyze financial risks Build predictive models focusing on customer scoring and service ranking Build a recommendation systems using SPSS on Apache Spark Tackle parallel computing and find out how it can support your machine learning projects Turn open data and communication data into actionable insights by making use of various forms of machine learning In Detail There's a reason why Apache Spark has become one of the most popular tools in Machine Learning – its ability to handle huge datasets at an impressive speed means you can be much more responsive to the data at your disposal. This book shows you Spark at its very best, demonstrating how to connect it with R and unlock maximum value not only from the tool but also from your data. Packed with a range of project "blueprints" that demonstrate some of the most interesting challenges that Spark can help you tackle, you'll find out how to use Spark notebooks and access, clean, and join different datasets before putting your knowledge into practice with some real-world projects, in which you will see how Spark Machine Learning can help you with everything from fraud detection to analyzing customer attrition. You'll also find out how to build a recommendation engine using Spark's parallel computing powers. Style and approach This book offers a step-by-step approach to setting up Apache Spark, and use other analytical tools with it to process Big Data and build machine learning projects.The initial chapters focus more on the theory aspect of machine learning with Spark, while each of the later chapters focuses on building standalone projects using Spark.

Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots

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Author : Dr. P. Kavitha
language : en
Publisher: Leilani Katie Publication
Release Date : 2023-12-23

Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots written by Dr. P. Kavitha 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 2023-12-23 with Computers categories.

Dr. P. Kavitha, Associate Professor, Department of Computer Science, Sri Ramakrishna College of Arts & Science, Coimbatore, Tamil Nadu, India. Mr. P. Jayasheelan, Assistant Professor, Department of Computer Science, Sri Krishna Aditya College of arts and Science, Coimbatore, Tamil Nadu, India. Ms. C. Karpagam, Assistant Professor, Department of Computer Science with Data Analytics, Dr. N.G.P. Arts and Science College, Coimbatore, Tamil Nadu, India. Dr. K. Prabavathy, Assistant Professor, Department of Data Science and Analytics, Sree Saraswathi Thyagaraja College, Pollachi, Coimbatore, Tamil Nadu, India.

Networks Of The Future

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Author : Mahmoud Elkhodr
language : en
Publisher: CRC Press
Release Date : 2017-10-16

Networks Of The Future written by Mahmoud Elkhodr and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-16 with Computers categories.

With the ubiquitous diffusion of the IoT, Cloud Computing, 5G and other evolved wireless technologies into our daily lives, the world will see the Internet of the future expand ever more quickly. Driving the progress of communications and connectivity are mobile and wireless technologies, including traditional WLANs technologies and low, ultra-power, short and long-range technologies. These technologies facilitate the communication among the growing number of connected devices, leading to the generation of huge volumes of data. Processing and analysis of such "big data" brings about many opportunities, as well as many challenges, such as those relating to efficient power consumptions, security, privacy, management, and quality of service. This book is about the technologies, opportunities and challenges that can drive and shape the networks of the future. Written by established international researchers and experts, Networks of the Future answers fundamental and pressing research challenges in the field, including architectural shifts, concepts, mitigation solutions and techniques, and key technologies in the areas of networking. The book starts with a discussion on Cognitive Radio (CR) technologies as promising solutions for improving spectrum utilization, and also highlights the advances in CR spectrum sensing techniques and resource management methods. The second part of the book presents the latest developments and research in the areas of 5G technologies and Software Defined Networks (SDN). Solutions to the most pressing challenges facing the adoption of 5G technologies are also covered, and the new paradigm known as Fog Computing is examined in the context of 5G networks. The focus next shifts to efficient solutions for future heterogeneous networks. It consists of a collection of chapters that discuss self-healing solutions, dealing with Network Virtualization, QoS in heterogeneous networks, and energy efficient techniques for Passive Optical Networks and Wireless Sensor Networks. Finally, the areas of IoT and Big Data are discussed, including the latest developments and future perspectives of Big Data and the IoT paradigms.

Complete Guide To Open Source Big Data Stack

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Author : Michael Frampton
language : en
Publisher: Apress
Release Date : 2018-01-18

Complete Guide To Open Source Big Data Stack written by Michael Frampton and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-18 with Computers categories.

See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack—sharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more. What You’ll Learn Install a private cloud onto the local cluster using Apache cloud stack Source, install, and configure Apache: Brooklyn, Mesos, Kafka, and Zeppelin See how Brooklyn can be used to install Mule ESB on a cluster and Cassandra in the cloud Install and use DCOS for big data processing Use Apache Spark for big data stack data processing Who This Book Is For Developers, architects, IT project managers, database administrators, and others charged with developing or supporting a big data system. It is also for anyone interested in Hadoop or big data, and those experiencing problems with data size.

Hands On Data Virtualization With Polybase

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Author : Pablo Alejandro Echeverria Barrios
language : en
Publisher: BPB Publications
Release Date : 2021-04-05

Hands On Data Virtualization With Polybase written by Pablo Alejandro Echeverria Barrios and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-05 with Computers categories.

Run queries and analysis on big data clusters across relational and non relational databases Ê KEY FEATURESÊÊ _ Connect to Hadoop, Azure, Spark, Oracle, Teradata, Cassandra, MongoDB, CosmosDB, MySQL, PostgreSQL, MariaDB, and SAP HANA. _ Numerous techniques on how to query data and troubleshoot Polybase for better data analytics. _ Exclusive coverage on Azure Synapse Analytics and building Big Data clusters. DESCRIPTIONÊ This book brings exciting coverage on establishing and managing data virtualization using polybase. This book teaches how to configure polybase on almost all relational and nonrelational databases. You will learn to set up the test environment for any tool or software instantly without hassle. You will practice how to design and build some of the high performing data warehousing solutions and that too in a few minutes of time. You will almost become an expert in connecting to all databases including hadoop, cassandra, MySQL, PostgreSQL, MariaDB and Oracle database. This book also brings exclusive coverage on how to build data clusters on Azure and using Azure Synapse Analytics. By the end of this book, you just don't administer the polybase for managing big data clusters but rather you learn to optimize and boost the performance for enabling data analytics and ease of data accessibility. WHAT YOU WILL LEARN _ Learn to configure Polybase and process Transact SQL queries with ease. _ Create a Docker container with SQL Server 2019 on Windows and Polybase. _ Establish SQL Server instance with any other software or tool using Polybase _ Connect with Cassandra, MongoDB, MySQL, PostgreSQL, MariaDB, and IBM DB2. WHO THIS BOOK IS FORÊÊ This book is for database developers and administrators familiar with the SQL language and command prompt. Managers and decision-makers will also find this book useful. No prior knowledge of any other technology or language is required. TABLE OF CONTENTS 1. What is Data Virtualization (Polybase) 2. History of Polybase 3. Polybase current state 4. Differences with other technologies 5. Usage 6. Future 7. SQL Server 8. Hadoop Cloudera and Hortonworks 9. Windows Azure Storage Blob 10. Spark 11. From Azure Synapse Analytics 12. From Big Data Clusters 13. Oracle 14. Teradata 15. Cassandra 16. MongoDB 17. CosmosDB 18. MySQL 19. PostgreSQL 20. MariaDB 21. SAP HANA 22. IBM DB2 23. Excel