Zeppelin For Interactive Data Analytics
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Zeppelin for Interactive Data Analytics
"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
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
Author: Dr. Jugnesh Kumar
language: en
Publisher: BPB Publications
Release Date: 2024-03-05
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