Data Engineering Fundamentals
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Data Engineering Fundamentals
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Author : Zhaolong Liu
language : en
Publisher: BPB Publications
Release Date : 2025-03-30
Data Engineering Fundamentals written by Zhaolong Liu and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-30 with Computers categories.
DESCRIPTION In today’s data-driven world, mastering data engineering is crucial for anyone looking to build robust data pipelines and extract valuable insights. This book simplifies complex concepts and provides a clear pathway to understanding the core principles that power modern data solutions. It bridges the gap between raw data and actionable intelligence, making data engineering accessible to everyone. This book walks you through the entire data engineering lifecycle. Starting with foundational concepts and data ingestion from diverse sources, you will learn how to build efficient data lakes and warehouses. You will learn data transformation using tools like Apache Spark and the orchestration of data workflows with platforms like Airflow and Argo Workflow. Crucial aspects of data quality, governance, scalability, and performance monitoring are thoroughly covered, ensuring you understand how to maintain reliable and efficient data systems. Real-world use cases across industries like e-commerce, finance, and government illustrate practical applications, while a final section explores emerging trends such as AI integration and cloud advancements. By the end of this book, you will have a solid foundation in data engineering, along with practical skills to help enhance your career. You will be equipped to design, build, and maintain data pipelines, transforming raw data into meaningful insights. WHAT YOU WILL LEARN ● Understand data engineering base concepts and build scalable solutions. ● Master data storage, ingestion, and transformation. ● Orchestrates data workflows and automates pipelines for efficiency. ● Ensure data quality, governance, and security compliance. ● Monitor, optimize, and scale data solutions effectively. ● Explore real-world use cases and future data trends. WHO THIS BOOK IS FOR This book is for aspiring data engineers, analysts, and developers seeking a foundational understanding of data engineering. Whether you are a beginner or looking to deepen your expertise, this book provides you with the knowledge and tools to succeed in today’s data engineering challenges. TABLE OF CONTENTS 1. Understanding Data Engineering 2. Data Ingestion and Acquisition 3. Data Storage and Management 4. Data Transformation and Processing 5. Data Orchestration and Workflows 6. Data Governance Principles 7. Scaling Data Solutions 8. Monitoring and Performance 9. Real-world Data Engineering Use Cases 10. Future Trends in Data Engineering
97 Things Every Data Engineer Should Know
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Author : Tobias Macey
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-06-11
97 Things Every Data Engineer Should Know written by Tobias Macey and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-11 with Computers categories.
Take advantage of the sky-high demand for data engineers today. With this in-depth book, current and aspiring engineers will learn powerful, real-world best practices for managing data big and small. Contributors from Google, Microsoft, IBM, Facebook, Databricks, and GitHub share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey from MIT Open Learning, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Projects include: Building pipelines Stream processing Data privacy and security Data governance and lineage Data storage and architecture Ecosystem of modern tools Data team makeup and culture Career advice.
Fundamentals Of Data Engineering
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Author : Joe Reis
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-06-22
Fundamentals Of Data Engineering written by Joe Reis and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-22 with Computers categories.
"Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you will learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available in the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You will understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, governance, and deployment that are critical in any data environment regardless of the underlying technology. This book will help you: Assess data engineering problems using an end-to-end data framework of best practices Cut through marketing hype when choosing data technologies, architecture, and processes Use the data engineering lifecycle to design and build a robust architecture Incorporate data governance and security across the data engineering lifecycle." - from Publisher.
Data Engineering With Google Cloud Platform
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Author : Adi Wijaya
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-03-31
Data Engineering With Google Cloud Platform written by Adi Wijaya 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 2022-03-31 with Computers categories.
Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineer Key Features Understand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solution Learn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelines Discover tips to prepare for and pass the Professional Data Engineer exam Book DescriptionWith this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards. Starting with a quick overview of the fundamental concepts of data engineering, you'll learn the various responsibilities of a data engineer and how GCP plays a vital role in fulfilling those responsibilities. As you progress through the chapters, you'll be able to leverage GCP products to build a sample data warehouse using Cloud Storage and BigQuery and a data lake using Dataproc. The book gradually takes you through operations such as data ingestion, data cleansing, transformation, and integrating data with other sources. You'll learn how to design IAM for data governance, deploy ML pipelines with the Vertex AI, leverage pre-built GCP models as a service, and visualize data with Google Data Studio to build compelling reports. Finally, you'll find tips on how to boost your career as a data engineer, take the Professional Data Engineer certification exam, and get ready to become an expert in data engineering with GCP. By the end of this data engineering book, you'll have developed the skills to perform core data engineering tasks and build efficient ETL data pipelines with GCP.What you will learn Load data into BigQuery and materialize its output for downstream consumption Build data pipeline orchestration using Cloud Composer Develop Airflow jobs to orchestrate and automate a data warehouse Build a Hadoop data lake, create ephemeral clusters, and run jobs on the Dataproc cluster Leverage Pub/Sub for messaging and ingestion for event-driven systems Use Dataflow to perform ETL on streaming data Unlock the power of your data with Data Studio Calculate the GCP cost estimation for your end-to-end data solutions Who this book is for This book is for data engineers, data analysts, and anyone looking to design and manage data processing pipelines using GCP. You'll find this book useful if you are preparing to take Google's Professional Data Engineer exam. Beginner-level understanding of data science, the Python programming language, and Linux commands is necessary. A basic understanding of data processing and cloud computing, in general, will help you make the most out of this book.
Data Engineering Fundamentals
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Author : Sandeep Kumar Pandey
language : en
Publisher: Notion Press
Release Date : 2024-08-28
Data Engineering Fundamentals written by Sandeep Kumar Pandey and has been published by Notion Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-28 with Education categories.
Data Engineering Fundamental: A Step by Step Approach Unlock the Power of Data with Practical Guidance from a Data Engineering Expert In today's data-driven world, organizations thrive on the ability to harness, process, and analyze data effectively. Data Engineering Fundamental: A Step by Step Approach is the ultimate guide for aspiring data engineers, data analysts, and professionals seeking to build a robust foundation in data engineering. This comprehensive book breaks down the core concepts of data engineering, offering a practical, hands-on approach to mastering key tools and techniques. From data pipelines and ETL processes to cloud technologies and database optimization, you'll explore a wide range of topics essential for managing and transforming data at scale. Key features include: Real-World Case Studies: Apply your learning to scenarios faced by data engineers in leading industries. Step-by-Step Guides: Detailed instructions to walk you through complex data engineering processes. Tool Mastery: In-depth coverage of popular platforms such as AWS, Azure, Databricks, and SQL databases. Best Practices: Learn how to design, optimize, and maintain efficient data pipelines.
Data Engineering With Python Sql 2025 Edition
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Author : Diego Rodrigues
language : en
Publisher: Diego Rodrigues
Release Date : 2025-01-01
Data Engineering With Python Sql 2025 Edition written by Diego Rodrigues and has been published by Diego Rodrigues this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-01 with Business & Economics categories.
Welcome to "DATA ENGINEERING WITH PYTHON AND SQL: Build Scalable Data Pipelines - 2025 Edition," a comprehensive and essential guide for professionals and students who wish to master the art of data engineering in a data-driven world. This book, written by Diego Rodrigues, a best-selling author with over 180 titles published in six languages, combines theory and practice to empower you in building efficient and scalable pipelines. Python and SQL are indispensable tools for data engineers, enabling precise manipulation, integration, and optimization of data workflows. Throughout this book, you will be guided through fundamental and advanced topics, exploring everything from the basics of data engineering to sophisticated strategies for security, governance, and automation of pipelines in both on-premises and cloud environments. Each chapter has been carefully designed to provide practical and applied understanding. You will learn to design database schemas, implement robust ETLs, automate workflows with frameworks such as Apache Airflow, and optimize SQL queries for high performance. Moreover, the book covers emerging topics like DataOps, API integration, and the use of Big Data tools such as Hadoop and Spark. With practical examples, detailed scripts, and clear explanations, "DATA ENGINEERING WITH PYTHON AND SQL" is more than just a technical manual; it is a gateway to a transformative career in the data field. Get ready to stand out in a competitive market and propel your professional journey. Your transformation in data engineering begins now! 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 mysql
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
A Practical Guide To Data Engineering
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Author : Pedram Ariel Rostami
language : en
Publisher: Starseed AI
Release Date :
A Practical Guide To Data Engineering written by Pedram Ariel Rostami and has been published by Starseed AI this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.
"A Practical Guide to Machine Learning and AI: Part-I" is an essential resource for anyone looking to dive into the world of artificial intelligence and machine learning. Whether you're a complete beginner or have some experience in the field, this book will equip you with the fundamental knowledge and hands-on skills needed to harness the power of these transformative technologies. In this comprehensive guide, you'll embark on an engaging journey that starts with the basics of data engineering. You'll gain a solid understanding of big data, the key roles involved, and how to leverage the versatile Python programming language for data-centric tasks. From mastering Python data types and control structures to exploring powerful libraries like NumPy and Pandas, you'll build a strong foundation to tackle more advanced concepts. As you progress, the book delves into the realm of exploratory data analysis (EDA), where you'll learn techniques to clean, transform, and extract insights from your data. This sets the stage for the heart of the book - machine learning. You'll explore both supervised and unsupervised learning, diving deep into regression, classification, clustering, and dimensionality reduction algorithms. Along the way, you'll encounter real-world examples and hands-on exercises to reinforce your understanding and apply what you've learned. But this book goes beyond just the technical aspects. It also addresses the ethical considerations surrounding machine learning, ensuring you develop a well-rounded perspective on the responsible use of these powerful tools. Whether your goal is to jumpstart a career in data science, enhance your existing skills, or simply satisfy your curiosity about the latest advancements in AI, "A Practical Guide to Machine Learning and AI: Part-I" is your comprehensive companion. Prepare to embark on an enriching journey that will equip you with the knowledge and skills to navigate the exciting frontiers of artificial intelligence and machine learning.
Engineering Fundamentals
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Author : Roger Timings
language : en
Publisher: Routledge
Release Date : 2007-06-07
Engineering Fundamentals written by Roger Timings and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-07 with Technology & Engineering categories.
Engineering Fundamentals is designed to meet the latest course requirements, and brings together the essential material from Roger Timings' previous engineering texts: Fundamentals of Mechanical Engineering, Fundamentals of Engineering, Basic Engineering Technology and General Engineering. A highly readable text is supported by numerous illustrations, learning objectives and exercises at the end of each chapter, making Engineering Fundamentals a complete student-focused course that is ideal for classroom, workshop and independent study.
Fundamentals Of Data Engineering Essential Guide
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Author : Versatile Reads
language : en
Publisher: Independently Published
Release Date : 2025-06-03
Fundamentals Of Data Engineering Essential Guide written by Versatile Reads and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-03 with Computers categories.
Fundamentals of Data Engineering - Essential Guide Master the Core Concepts of Data Engineering - The Backbone of Modern Data-Driven Enterprises Are you ready to break into the fast-growing world of data engineering or strengthen your foundational knowledge with an all-in-one, concise, and expertly crafted guide? This Essentials Guide on the Fundamentals of Data Engineering provides a comprehensive, beginner-friendly roadmap to understanding how raw data is transformed into powerful business insights. Whether you're a student, aspiring data engineer, data analyst, or tech-savvy professional, this book offers clear explanations and actionable insights across the entire data pipeline. What's Inside Chapter 01: Data Engineering Described - Grasp the role of data engineers in today's tech landscape. Chapter 02: The Data Engineering Lifecycle - Explore each phase of the modern data workflow. Chapter 03: Designing Good Data Architecture - Learn the key principles of scalable, reliable architecture. Chapter 04: Choosing Technologies - Compare tools and platforms across the lifecycle. Chapter 05-08: From Source to Transformation - Dive deep into data generation, storage, ingestion, and transformation techniques. Chapter 09: Serving Data for Analytics, ML & Reverse ETL - Unlock the real value of your data. Chapter 10: Security and Privacy - Build secure, compliant data systems. Chapter 11: The Future of Data Engineering - Stay ahead with trends like real-time processing and data mesh. Why This Guide Stands Out Written in clear, accessible language with real-world relevance Covers the entire lifecycle from data generation to consumption Helps you confidently explore career paths, tools, and techniques in data engineering A perfect companion for bootcamps, academic courses, or self-study Unlock the power of modern data workflows and take your first step into one of tech's most in-demand careers.