Big Data Fundamentals
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Big Data Fundamentals
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Author : Thomas Erl
language : en
Publisher: Prentice Hall
Release Date : 2015-12-29
Big Data Fundamentals written by Thomas Erl and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-29 with Computers categories.
“This text should be required reading for everyone in contemporary business.” --Peter Woodhull, CEO, Modus21 “The one book that clearly describes and links Big Data concepts to business utility.” --Dr. Christopher Starr, PhD “Simply, this is the best Big Data book on the market!” --Sam Rostam, Cascadian IT Group “...one of the most contemporary approaches I’ve seen to Big Data fundamentals...” --Joshua M. Davis, PhD The Definitive Plain-English Guide to Big Data for Business and Technology Professionals Big Data Fundamentals provides a pragmatic, no-nonsense introduction to Big Data. Best-selling IT author Thomas Erl and his team clearly explain key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. All coverage is supported with case study examples and numerous simple diagrams. The authors begin by explaining how Big Data can propel an organization forward by solving a spectrum of previously intractable business problems. Next, they demystify key analysis techniques and technologies and show how a Big Data solution environment can be built and integrated to offer competitive advantages. Discovering Big Data’s fundamental concepts and what makes it different from previous forms of data analysis and data science Understanding the business motivations and drivers behind Big Data adoption, from operational improvements through innovation Planning strategic, business-driven Big Data initiatives Addressing considerations such as data management, governance, and security Recognizing the 5 “V” characteristics of datasets in Big Data environments: volume, velocity, variety, veracity, and value Clarifying Big Data’s relationships with OLTP, OLAP, ETL, data warehouses, and data marts Working with Big Data in structured, unstructured, semi-structured, and metadata formats Increasing value by integrating Big Data resources with corporate performance monitoring Understanding how Big Data leverages distributed and parallel processing Using NoSQL and other technologies to meet Big Data’s distinct data processing requirements Leveraging statistical approaches of quantitative and qualitative analysis Applying computational analysis methods, including machine learning
Big Data Fundamentals A Comprehensive Guide To Data Management And Analysis
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Author : Dhruvitkumar Patel
language : en
Publisher: Academic Guru Publishing House
Release Date : 2024-08-27
Big Data Fundamentals A Comprehensive Guide To Data Management And Analysis written by Dhruvitkumar Patel and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-27 with Study Aids categories.
“Big Data Fundamentals: A Comprehensive Guide to Data Management and Analysis” aims to provide a complete knowledge of the basic ideas and methods related with big data. Ten thorough chapters, each with an emphasis on important aspects of big data including definition, features, technologies, processing methods, and security issues, make up the book. The book starts with an overview of big data and its impact on modern businesses then looks at many technologies and tools within the big data ecosystem. Readers will learn recommended practices for data management as well as data storage options—including data lakes and cloud storage. Discussions on data processing and analytics include batch and stream processing as well as methods like ETL. Emphasizing their importance in obtaining insightful analysis from large volumes of data, the book also investigates the junction of data mining and machine learning. It underlines the need for data visualization for efficient result interpretation and successful result communication. Analyzed are the security and privacy issues in the framework of big data, along with solutions for guaranteeing compliance and governance. The book presents advanced topics like real-time processing and future trends along with useful implementation techniques. This comprehensive handbook is a vital tool for anybody wishing to understand and use big data’s potential in their career.
Big Data
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Author : Rob Botwright
language : en
Publisher: Rob Botwright
Release Date : 2024
Big Data written by Rob Botwright and has been published by Rob Botwright this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Computers categories.
Uncover the secrets of Big Data with our comprehensive book bundle: "Big Data: Statistics, Data Mining, Analytics, and Pattern Learning." Dive into the world of data analytics and processing with Book 1, where you'll gain a solid understanding of the fundamentals necessary to navigate the vast landscape of big data. In Book 2, explore data mining techniques that allow you to extract valuable insights and patterns from large datasets. From marketing to finance and beyond, discover how to uncover hidden trends that drive informed decision-making. Ready to take your skills to the next level? Book 3 delves into advanced data science, where you'll learn to harness the power of machine learning for big data analysis. From regression analysis to neural networks, master the tools and techniques that drive predictive modeling and pattern recognition. Finally, in Book 4, learn how to design robust big data architectures that can scale to meet the needs of modern enterprises. Explore architectural patterns, scalability techniques, and fault tolerance mechanisms that ensure your systems are resilient and reliable. Whether you're a beginner looking to build a solid foundation or an experienced professional seeking to deepen your expertise, this book bundle has something for everyone. Don't miss out on this opportunity to unlock the potential of Big Data and drive innovation in your organization. Order now and embark on your journey to becoming a Big Data expert!
Principles Of Big Data
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Author : Jules J. Berman
language : en
Publisher: Newnes
Release Date : 2013-05-20
Principles Of Big Data written by Jules J. Berman and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-20 with Computers categories.
Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn how their data can be integrated with data from other resources, and how the data extracted from Big Data resources can be used for purposes beyond those imagined by the data creators. - Learn general methods for specifying Big Data in a way that is understandable to humans and to computers - Avoid the pitfalls in Big Data design and analysis - Understand how to create and use Big Data safely and responsibly with a set of laws, regulations and ethical standards that apply to the acquisition, distribution and integration of Big Data resources
Principles And Practice Of Big Data
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Author : Jules J. Berman
language : en
Publisher: Academic Press
Release Date : 2018-07-23
Principles And Practice Of Big Data written by Jules J. Berman and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-23 with Technology & Engineering categories.
Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information, Second Edition updates and expands on the first edition, bringing a set of techniques and algorithms that are tailored to Big Data projects. The book stresses the point that most data analyses conducted on large, complex data sets can be achieved without the use of specialized suites of software (e.g., Hadoop), and without expensive hardware (e.g., supercomputers). The core of every algorithm described in the book can be implemented in a few lines of code using just about any popular programming language (Python snippets are provided). Through the use of new multiple examples, this edition demonstrates that if we understand our data, and if we know how to ask the right questions, we can learn a great deal from large and complex data collections. The book will assist students and professionals from all scientific backgrounds who are interested in stepping outside the traditional boundaries of their chosen academic disciplines. - Presents new methodologies that are widely applicable to just about any project involving large and complex datasets - Offers readers informative new case studies across a range scientific and engineering disciplines - Provides insights into semantics, identification, de-identification, vulnerabilities and regulatory/legal issues - Utilizes a combination of pseudocode and very short snippets of Python code to show readers how they may develop their own projects without downloading or learning new software
Big Data And Data Science
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Author : Dhaanyalakshmi Ahuja
language : en
Publisher: Educohack Press
Release Date : 2025-01-03
Big Data And Data Science written by Dhaanyalakshmi Ahuja and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
Big Data and Data Science: Analytics for the Future dives into the fundamentals of big data and data science. We explain the data science life cycle and its major components, such as statistics and visualization, using various programming languages like R. As technology evolves, the significance of data science and big data analytics continues to grow, making this field increasingly important. Our book is designed in a reader-friendly manner, targeting newcomers to data science. Concepts are presented clearly and can be easily implemented through the procedures and algorithms provided. As data collection multiplies exponentially, analytics remains an evolving field with vast career opportunities. We cater to two types of readers: those skeptical about the benefits of big data and predictive analytics, and enthusiasts keen to explore current applications of these technologies. Big data is a fantastic choice for launching a career in IT, and this book equips you with the knowledge needed to succeed. We cover a broad spectrum of topics, ensuring a strong foundation in data science and big data analytics.
Sql For Big Data
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Author : Diego Rodrigues
language : en
Publisher: StudioD21
Release Date : 2025-02-09
Sql For Big Data written by Diego Rodrigues and has been published by StudioD21 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-09 with Business & Economics categories.
SQL FOR BIG DATA: Optimized Queries, Indexing, and Scalability is an essential guide for professionals and students who want to master the efficient handling of large volumes of data using SQL. In this book, you will explore advanced techniques for query optimization, indexing, and scalability, which are fundamental for tackling the challenges of Big Data environments. Written by Diego Rodrigues, a best-selling author with over 180 titles published in six languages, this book combines theory and practice to equip you with the skills to work with distributed databases, efficient modeling, and large-scale data processing. Throughout the chapters, you will learn how to structure data for maximum performance, use advanced indexes, implement intelligent partitioning, and integrate SQL with technologies like Hadoop and Spark. Additionally, the book covers security strategies, automation, and monitoring, preparing you to confidently face the challenges of the data market. With practical examples and in-depth insights, SQL FOR BIG DATA is more than just a technical manual—it is an indispensable resource for those seeking excellence in SQL usage in high-complexity scenarios. Get ready to take your skills to the next level and transform your approach to data processing! TAGS: Python Java Linux Kali HTML ASP.NET Ada Assembly BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Regression Logistic Regression Decision Trees Random Forests AI ML K-Means Clustering Support Vector Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF AWS Google Cloud IBM Azure Databricks Nvidia Meta Power BI IoT CI/CD Hadoop Spark Dask SQLAlchemy Web Scraping MySQL Big Data Science OpenAI ChatGPT Handler RunOnUiThread() Qiskit Q# Cassandra Bigtable VIRUS MALWARE Information Pen Test Cybersecurity Linux Distributions Ethical Hacking Vulnerability Analysis System Exploration Wireless Attacks Web Application Security Malware Analysis Social Engineering Social Engineering Toolkit SET Computer Science IT Professionals Careers Expertise Library Training Operating Systems Security Testing Penetration Test Cycle Mobile Techniques Industry Global Trends Tools Framework Network Security Courses Tutorials Challenges Landscape Cloud Threats Compliance Research Technology Flutter Ionic Web Views Capacitor APIs REST GraphQL Firebase Redux Provider Bitrise Actions Material Design Cupertino Fastlane Appium Selenium Jest Visual Studio AR VR sql deepseek mysql startup digital marketing
Big Data Management And Analytics
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Author : Rajesh Jugulum
language : en
Publisher: CRC Press
Release Date : 2025-06-30
Big Data Management And Analytics written by Rajesh Jugulum and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Computers categories.
As more companies go digital and conduct their business online, this book provides practical examples of how they can better manage their data and use it to generate maximum value. It offers an integrated approach by treating data as an asset and discusses how to preserve and protect it just like any other corporate asset. Big Data Management and Analytics: Concepts, Tools, and Applications illustrates effective strategies for managing, governing, and analyzing big data to gain a competitive edge for companies utilizing big data and analytics. It offers a comprehensive guide on methods, tools, and concepts to efficiently manage and analyze big data in order to make informed decisions. Additionally, this book explores the significance of artificial intelligence and machine learning in leveraging big data and how they can be optimized in a well-structured environment. This book also emphasizes treating big data as a valuable asset and outlines strategies for preserving and safeguarding it like any other corporate asset. The inclusion of case studies ensures that the methodologies and concepts presented can be easily implemented in day-to-day operations. Given the current significance of big data in the business world, this book equips readers with the necessary skills to effectively manage this valuable asset. It is tailored for practitioners, students, and professionals working in data mining, big data, and machine learning across various industries, including manufacturing.
Scaling Big Data Leveraging Llms For Enterprise Success
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Author : Vincent Kanka
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2024-04-29
Scaling Big Data Leveraging Llms For Enterprise Success written by Vincent Kanka and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-29 with Business & Economics categories.
As enterprises navigate an increasingly data-driven world, the integration of Large Language Models (LLMs) into big data pipelines offers transformative opportunities. Scaling Big Data: Leveraging LLMs for Enterprise Success serves as a comprehensive guide for IT leaders, data scientists, and executives seeking to harness LLMs for superior analytics and decision-making. This book delves into the intersection of LLMs and big data, exploring how enterprises can scale operations while enhancing agility and insight extraction. Readers will uncover practical strategies for integrating LLMs with traditional tools like Apache Spark and Hadoop, optimizing infrastructure for real-time data processing, and employing RAG-based architectures to refine query systems. From cloud-based deployments to on-premise solutions, this guide provides actionable frameworks for building scalable, secure, and efficient systems tailored to industry-specific needs. Real-world case studies demonstrate how LLMs revolutionize workflows in finance, healthcare, marketing, and more, showcasing their ability to deliver precise, context-rich insights at scale. This book also addresses challenges such as ensuring data privacy, achieving low latency in pipelines, and navigating compliance landscapes. Emerging trends, including multi-modal LLM applications and AI- driven automation, are explored, preparing readers to stay ahead in a rapidly evolving technological landscape. Whether streamlining analytics, enhancing decision-making, or driving innovation, Scaling Big Data equips professionals with the tools to transform their enterprises and thrive in a competitive digital era.
Privacy And Security Policies In Big Data
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Author : Tamane, Sharvari
language : en
Publisher: IGI Global
Release Date : 2017-03-03
Privacy And Security Policies In Big Data written by Tamane, Sharvari and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-03 with Computers categories.
In recent years, technological advances have led to significant developments within a variety of business applications. In particular, data-driven research provides ample opportunity for enterprise growth, if utilized efficiently. Privacy and Security Policies in Big Data is a pivotal reference source for the latest research on innovative concepts on the management of security and privacy analytics within big data. Featuring extensive coverage on relevant areas such as kinetic knowledge, cognitive analytics, and parallel computing, this publication is an ideal resource for professionals, researchers, academicians, advanced-level students, and technology developers in the field of big data.