Data Engineering On The Cloud A Practical Guide 2025
DOWNLOAD
Download Data Engineering On The Cloud A Practical Guide 2025 PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Data Engineering On The Cloud A Practical Guide 2025 book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Data Engineering On The Cloud A Practical Guide 2025
DOWNLOAD
Author : Raghu Gopa, Dr. Arpita Roy
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Data Engineering On The Cloud A Practical Guide 2025 written by Raghu Gopa, Dr. Arpita Roy and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE The digital transformation of businesses and the exponential growth of data have created a fundamental shift in how organizations approach data management, analytics, and decision-making. As cloud technologies continue to evolve, cloud-based data engineering has become central to the success of modern data-driven enterprises. “Data Engineering on the Cloud: A Practical Guide” aims to equip data professionals, engineers, and organizations with the knowledge and practical tools needed to build and manage scalable, secure, and efficient data engineering pipelines in cloud environments. This book is designed to bridge the gap between the theoretical foundations of data engineering and the practical realities of working with cloud-based data platforms. Cloud computing has revolutionized data storage, processing, and analytics by offering unparalleled scalability, flexibility, and cost efficiency. However, with these opportunities come new challenges, including selecting the right tools, architectures, and strategies to ensure seamless data integration, transformation, and delivery. As businesses increasingly migrate their data to the cloud, it is essential for data engineers to understand how to leverage the capabilities of the cloud to build robust data pipelines that can handle large, complex datasets in real-time. Throughout this guide, we will explore the various facets of cloud-based data engineering, from understanding cloud storage and computing services to implementing data integration techniques, managing data quality, and optimizing performance. Whether you are building data pipelines from scratch, migrating on-premises systems to the cloud, or enhancing existing data workflows, this book will provide actionable insights and step-by-step guidance on best practices, tools, and frameworks commonly used in cloud data engineering. Key topics covered in this book include: · The fundamentals of cloud architecture and the role of cloud providers (such as AWS, Google Cloud, and Microsoft Azure) in data engineering workflows. · Designing scalable and efficient data pipelines using cloud-based tools and services. · Integrating diverse data sources, including structured, semi-structured, and unstructured data, for seamless processing and analysis. · Data transformation techniques, including ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform), in cloud environments. · Ensuring data quality, governance, and security when working with cloud data platforms. · Optimizing performance for data storage, processing, and analytics to handle growing data volumes and complexity. This book is aimed at professionals who are already familiar with data engineering concepts and are looking to apply those concepts within cloud environments. It is also suitable for organizations that are in the process of migrating to cloud-based data platforms and wish to understand the nuances and best practices for cloud data engineering. In addition to theoretical knowledge, this guide emphasizes hands-on approaches, providing practical examples, code snippets, and real-world case studies to demonstrate the effective implementation of cloud-based data engineering solutions. We will explore how to utilize cloud-native services to streamline workflows, improve automation, and reduce manual interventions in data pipelines. Throughout the book, you will gain insights into the evolving tools and technologies that make data engineering more agile, reliable, and efficient. The role of data engineering is growing ever more important in enabling businesses to unlock the value of their data. By the end of this book, you will have a comprehensive understanding of how to leverage cloud technologies to build high-performance, scalable data engineering solutions that are aligned with the needs of modern data-driven organizations. We hope this guide helps you to navigate the complexities of cloud data engineering and helps you unlock new possibilities for your data initiatives. Welcome to “Data Engineering on the Cloud: A Practical Guide.” Let’s embark on this journey to harness the full potential of cloud technologies in the world of data engineering. Authors
Cloud First Data Engineering Architecting Scalable Pipelines And Analytics With Aws 2025
DOWNLOAD
Author : Author:1- PEEYUSH PATEL Author:2 -DR. MANMOHAN SHARMA
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Cloud First Data Engineering Architecting Scalable Pipelines And Analytics With Aws 2025 written by Author:1- PEEYUSH PATEL Author:2 -DR. MANMOHAN SHARMA and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Author:1- PEEYUSH PATEL Author:2 -DR. MANMOHAN SHARMA ISBN - 978-93-6788-817-9 Preface In today’s digital economy, organizations generate more data in a single day than many legacy systems could process in years. The shift to cloud-first architectures has transformed how we collect, store, and analyze information—enabling businesses to respond faster to market changes, scale without upfront hardware investments, and foster innovation across teams. This book, Cloud-First Data Engineering: Architecting Scalable Pipelines and Analytics with AWS, is written for data engineers, architects, and technical leaders who seek to design robust, high-performing data platforms using Amazon Web Services. Over the past decade, AWS has introduced a rich portfolio of data services—ranging from serverless ETL (AWS Glue) and streaming solutions (Kinesis, MSK) to petabyte-scale analytics (Redshift, Athena) and machine learning integrations (SageMaker). Yet, with such breadth comes complexity: selecting the right components, designing for cost efficiency, maintaining security and compliance, and ensuring operational excellence are constant challenges. This book distills best practices, architectural patterns, and real-world examples into a cohesive roadmap. You will learn how to build end-to-end pipelines that evolve with your data volume, implement modern data Lakehouse strategies, enable real-time insights, and incorporate governance at every layer. Chapters progress from foundational concepts—such as cloud-first paradigms and core AWS data services—to advanced topics like Data Mesh, serverless Lakehouse’s, generative AI for data quality, and emerging roles in data organization. Each section demystifies the trade-offs, illustrates implementation steps, and highlights pitfalls to avoid. Whether you are migrating legacy workloads, optimizing existing pipelines, or pioneering new analytics capabilities, this book serves as both a practical guide and strategic playbook to navigate the ever-changing landscape of cloud data engineering on AWS. Authors
Data Engineering With Google Cloud Platform
DOWNLOAD
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.
Cloud Native Financial Data Engineering Principles Pipelines And Scalable Architectures 2025
DOWNLOAD
Author : Author1:- ANOOP PURUSHOTAMAN, Author2:- PROF. DR M K SHARMA
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Cloud Native Financial Data Engineering Principles Pipelines And Scalable Architectures 2025 written by Author1:- ANOOP PURUSHOTAMAN, Author2:- PROF. DR M K SHARMA and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE The financial services industry has undergone a profound transformation over the past decade. From high-frequency trading firms demanding millisecond-level insights to retail banks seeking richer, personalized customer analytics, the scale, velocity, and variety of financial data have exploded. Traditional on-premises data warehouses and batch-oriented ETL pipelines struggle to keep pace with today’s requirements for real-time risk monitoring, fraud detection, algorithmic trading signals, and regulatory reporting. In parallel, the rise of cloud computing has unlocked virtually unlimited storage and compute capacity, democratized access to sophisticated analytics tools, and fostered an ecosystem of serverless and managed services designed for elasticity and resilience. This book, Cloud-Native Financial Data Engineering: Principles, Pipelines, and Scalable Architectures, is born out of the need to bridge these trends. It is written for data engineers, architects, and technology leaders who are tasked with designing and operating the next generation of financial data platforms. Whether you are building a streaming pipeline to ingest market quotes, an event-driven system to detect anomalous trading patterns, or a unified data lake that brings together transaction, customer, and risk data, the cloud offers a paradigm shift: you can focus on business logic and analytical value, rather than on undifferentiated heavy lifting of infrastructure. In the chapters that follow, we first establish the foundational principles of cloud-native data engineering in a financial context. We examine how to decompose monolithic ETL workflows into micro-services and pipelines, how to embrace immutable, append-only event stores, and how to design for failure and recovery at every layer. We then explore the core building blocks of modern data architecture: data ingestion patterns (batch, stream, change-data capture), transformation frameworks (serverless functions, containerized jobs, SQL-on-data-lake), metadata management, and orchestration engines. Along the way, we emphasize best practices for security, governance, and cost optimization—imperatives in a regulated, risk-averse industry. Subsequent sections dive into specialized topics that address the unique demands of financial workloads. We cover real-time analytics use cases such as market data enrichment, fraud-signal propagation, and credit-scoring model deployment. We unpack architectural patterns for high-throughput, low-latency pipelines—leveraging managed streaming platforms, serverless compute, column-arithmetic engines, and cloud-native message buses. We also address data quality and lineage at scale, showing how to embed continuous validation tests and visibility into every pipeline stage, thereby ensuring that trading strategies and risk models rest on a bedrock of trusted data. A recurring theme throughout this book is scalability: both horizontal scalability of compute and storage, and organizational scalability via self-service data platforms. We explore how to enable “data as a product” within your enterprise—providing domain teams with curated, discoverable datasets, APIs, and developer tooling so they can build analytics and machine-learning solutions without reinventing ingestion pipelines or wrestling with infrastructure details. This shift not only accelerates time to insight but also frees centralized engineering teams to focus on platform reliability, cost governance, and feature innovation. By combining conceptual frameworks with concrete, provider-agnostic examples, this book aims to be both a roadmap and a practical guide. Wherever possible, we illustrate patterns with code snippets and architectural diagrams, while also pointing to managed services offered by leading cloud providers. We encourage you to adapt these patterns to your organization’s existing standards and to rigorously validate them within your security and compliance constraints. As the lines between “finance” and “technology” continue to blur, the ability to engineer data pipelines that are resilient, elastic, and observably sound becomes a strategic differentiator. Whether you are modernizing a legacy data warehouse, building a next-gen risk platform, or architecting a real-time trading analytics engine, the cloud-native principles and patterns in this volume will equip you to deliver robust, cost-effective solutions that meet the exact demands of financial markets and regulatory bodies alike. We extend our gratitude to the practitioners, open-source contributors, and early adopters whose insights and feedback have shaped this book. It is our hope that by sharing these learnings, we collectively raise the bar for financial data engineering and help usher in an era where data-driven decisions can be made with confidence, speed, and scale. Authors
Kubernetes For Data Engineers Orchestrating Big Data And Ai Pipelines 2025
DOWNLOAD
Author : Author:1- KARAN SINGH ALANG, Author:1- Dr RUPESH MISHRA
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Kubernetes For Data Engineers Orchestrating Big Data And Ai Pipelines 2025 written by Author:1- KARAN SINGH ALANG, Author:1- Dr RUPESH MISHRA and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In today’s rapidly evolving world of data engineering, the need for scalable, efficient, and reliable infrastructure has never been more critical. With the advent of big data, artificial intelligence (AI), and machine learning (ML), the complexity of managing and deploying sophisticated data pipelines has grown exponentially. Enter Kubernetes, the open-source platform that has redefined how applications are deployed, scaled, and managed across a distributed environment. Kubernetes for Data Engineers: Orchestrating Big Data and AI Pipelines is written for data engineers, architects, and technologists who seek to leverage the power of Kubernetes in the realm of data processing and AI/ML workflows. This book serves as a practical guide for mastering the skills necessary to efficiently manage large-scale data workloads, while also offering insights into Kubernetes’ core features and its application to data-intensive tasks. Throughout this book, we explore how Kubernetes can help streamline the deployment, management, and scaling of big data technologies and AI/ML pipelines, enabling you to manage diverse tools like Hadoop, Spark, TensorFlow, and more, all within a Kubernetes environment. By adopting Kubernetes’ orchestration and automation capabilities, data engineers can drive performance, reduce overhead, and ensure resilience across the data processing lifecycle. In addition to covering fundamental Kubernetes concepts, we will also dive deep into the specific challenges faced by data engineers and how Kubernetes addresses them. From managing containerized services for distributed systems to automating data pipelines, this book will walk you through hands-on examples, case studies, and best practices to ensure you can effectively apply these concepts in your own projects. As data engineering becomes more intricate and interwoven with AI-driven innovations, the demand for Kubernetes skills will continue to rise. Whether you are already familiar with Kubernetes or just beginning to
Mastering Oracle Cloud Erp A Practical Guide To Implementation Integrations And Optimization 2025
DOWNLOAD
Author : Mukesh Garg, Dr Vandna Bansla
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Mastering Oracle Cloud Erp A Practical Guide To Implementation Integrations And Optimization 2025 written by Mukesh Garg, Dr Vandna Bansla and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE Mastering Oracle Cloud ERP: A Practical Guide to Implementation, Integrations, and Optimization is designed to be a comprehensive and hands-on resource for professionals seeking to understand and master Oracle’s Enterprise Resource Planning (ERP) solution in the cloud. As businesses continue to adapt to rapidly evolving technological landscapes, the need for agile, scalable, and integrated ERP systems has never been more critical. Oracle Cloud ERP offers organizations the tools necessary to streamline operations, enhance decision-making, and drive business growth. This book is written to provide readers with a practical understanding of how to successfully implement, integrate, and optimize Oracle Cloud ERP to unlock its full potential. In recent years, cloud-based solutions have become the backbone of many enterprise IT systems, replacing traditional on-premises software with scalable, flexible solutions. Oracle’s Cloud ERP has emerged as one of the most widely adopted systems, offering a range of integrated applications that cater to different aspects of business management, including financials, procurement, supply chain management, and human resources. The shift to cloud computing allows organizations to simplify their infrastructure, reduce costs, and maintain agility while ensuring that their systems are always up to date with the latest innovations. This book serves as a practical guide for both beginners and experienced professionals, providing a step-by-step approach to implementing Oracle Cloud ERP. It covers the implementation process, from initial planning and system configuration to full deployment, ensuring that the reader has a clear understanding of how to set up the system in a way that aligns with business goals. Each chapter is designed to guide readers through the complexities of Oracle Cloud ERP, offering detailed insights into how to structure and execute an effective implementation strategy. The integration of Oracle Cloud ERP with existing systems is another critical area covered in this book. As organizations increasingly rely on multiple platforms for different functions, integration becomes essential for ensuring that data flows seamlessly between systems. Whether integrating with legacy applications, third-party tools, or other Oracle solutions, this book outlines best practices for building and maintaining a robust integration framework that supports business operations and ensures data consistency. Beyond implementation and integration, this guide emphasizes optimization—helping readers learn how to continuously improve and maximize the value of Oracle Cloud ERP over time. With constant updates and innovations from Oracle, organizations need to be able to effectively adapt their ERP systems to meet changing business needs. The book offers practical strategies for monitoring system performance, troubleshooting common challenges, and leveraging Oracle Cloud’s advanced capabilities, such as AI and automation, to streamline processes and drive operational efficiency. Real-world case studies and practical examples throughout the book demonstrate how successful Oracle Cloud ERP implementations have transformed businesses across various industries. These examples illustrate key lessons learned and provide actionable insights that can be applied to real-world scenarios, making this book an invaluable resource for anyone involved in the Oracle Cloud ERP journey. Whether you are an IT professional, a project manager, a business analyst, or a consultant working on Oracle Cloud ERP projects, this book will equip you with the knowledge and tools needed to implement, integrate, and optimize Oracle Cloud ERP systems effectively. Our goal is not only to help you understand the technical aspects but also to provide a framework for using Oracle Cloud ERP as a strategic asset that drives business performance. In conclusion, Mastering Oracle Cloud ERP is not just a book about technology, it’s a guide to leveraging Oracle’s ERP solution to achieve business success in the digital age. With a solid foundation in both the technical and strategic aspects of implementation, integration, and optimization, this book is designed to help you navigate the complexities of Oracle Cloud ERP and unlock its full potential. Authors
C Algorithms For New Programmers A Practical Guide With Examples
DOWNLOAD
Author : William E. Clark
language : en
Publisher: Walzone Press
Release Date : 2025-04-06
C Algorithms For New Programmers A Practical Guide With Examples written by William E. Clark and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-06 with Computers categories.
Explore the foundational principles of C# programming with "C# Algorithms for New Programmers: A Practical Guide with Examples." This book offers an in-depth tutorial for newcomers and those looking to refine their programming skills. Beginning with a clear introduction to the C# language and the .NET ecosystem, it equips readers with the essential understanding required to navigate the world of modern software development. This text stands as an invaluable resource for anyone eager to construct a strong foundation in programming concepts and techniques. Covering a broad spectrum of topics, this book leads readers through the intricacies of data management, operators, control flow, and advanced programming techniques. From initial variable declarations to comprehensive coverage of object-oriented programming, readers will garner the expertise needed to employ efficient programming practices effectively. Key areas such as asynchronous programming, data structures, algorithms, error handling, and file operations are explored in detail, ensuring that readers are well-prepared for both academic and professional pursuits. Authored by William E. Clark, an experienced educator in the field of computer science, this guide demystifies complex concepts with clarity and precision. Combined with practical examples and exercises, it empowers readers to apply theory in real-world scenarios. Whether embarking on a new programming journey or seeking to refine existing skills, this book provides a thorough and concise pathway to mastery in C# programming.
Arrier Certification And Field Testing In The 5g Era A Practical Guide For Engineers And Managers 2025
DOWNLOAD
Author : Author :1-Kranthi Kiran Kusuma, Author :2- Dr. Anand Singh
language : en
Publisher: RAVEENA PRAKASHAN OPC PVT LTD
Release Date :
Arrier Certification And Field Testing In The 5g Era A Practical Guide For Engineers And Managers 2025 written by Author :1-Kranthi Kiran Kusuma, Author :2- Dr. Anand Singh and has been published by RAVEENA PRAKASHAN OPC PVT LTD this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE The rapid evolution of wireless technology has led to the transformative era of 5G, which promises to revolutionize industries, redefine connectivity, and drive the development of innovative applications across various sectors, including telecommunications, healthcare, automotive, entertainment, and beyond. As 5G networks are deployed worldwide, the demand for high-quality and reliable wireless services has never been greater. This is where carrier certification and field testing play a pivotal role in ensuring that 5G networks meet the stringent performance standards required for such a change in basic assumptions. “Carrier Certification and Field Testing in the 5G Era: A Practical Guide for Engineers and Managers” is written to serve as a comprehensive resource for professionals navigating the complexities of 5G network testing, certification, and deployment. The book addresses the vital role of testing and certification in the success of 5G services, offering practical insights into the strategies, tools, and methodologies required to verify the performance, functionality, and interoperability of 5G systems. Whether you are an engineer tasked with the technical aspects of testing or a manager overseeing the deployment of 5G services, this book provides valuable guidance on the entire certification process, from initial design and lab testing to real-world field trials. In this book, we cover a wide range of topics crucial to 5G network performance validation. We explore the technical aspects of field testing, including signal quality, throughput, latency, and reliability measurements. We also delve into the testing of new 5G technologies, such as millimeter-wave frequencies, massive MIMO (multiple-input, multiple-output), and network slicing. Additionally, the book examines the importance of carrier certification programs, the role of industry standards, and the critical need for collaboration between network operators, equipment vendors, and regulatory bodies to ensure a seamless 5G experience for end users. As the transition from 4G to 5G presents both opportunities and challenges, this guide is designed to equip professionals with the knowledge needed to navigate the technical, operational, and managerial aspects of 5G field testing and certification. The book is intended for engineers, network planners, testers, project managers, and executives who need to understand the intricacies of 5G network validation and the practical challenges involved in ensuring that 5G networks meet the rigorous performance standards set by industry stakeholders. The content is presented in a way that balances both technical depth and accessibility. While it includes detailed explanations of measurement techniques, testing procedures, and equipment, it also offers practical Carrier Certification and Field Testing in the 5G Era: A Practical Guide for Engineers and Managers insights and case studies to help professionals understand how to apply these concepts in real-world scenarios. By incorporating lessons learned from field tests and certification processes, the book provides a well-rounded perspective on the current state of 5G testing and offers a roadmap for future advancements. As 5G continues to shape the future of connectivity, ensuring the reliable performance of 5G networks is paramount. Through this book, we hope to empower engineers and managers with the tools and knowledge necessary to contribute to the successful deployment and optimization of 5G networks, paving the way for the next generation of wireless technology. We invite you to explore this guide and deepen your understanding of carrier certification and field testing in the 5G era. Authors Author :1-Kranthi Kiran Kusuma Author :2- Dr. Anand Singh
Aws Certified Data Engineer Study Guide
DOWNLOAD
Author : Syed Humair
language : en
Publisher: John Wiley & Sons
Release Date : 2025-03-13
Aws Certified Data Engineer Study Guide written by Syed Humair 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 2025-03-13 with Computers categories.
Your complete Guide to preparing for the AWS® Certified Data Engineer: Associate exam The AWS® Certified Data Engineer Study Guide is your one-stop resource for complete coverage of the challenging DEA-C01 Associate exam. This Sybex Study Guide covers 100% of the DEA-C01 objectives. Prepare for the exam faster and smarter with Sybex thanks to accurate content including, an assessment test that validates and measures exam readiness, real-world examples and scenarios, practical exercises, and challenging chapter review questions. Reinforce and retain what you’ve learned with the Sybex online learning environment and test bank, accessible across multiple devices. Get ready for the AWS Certified Data Engineer exam – quickly and efficiently – with Sybex. Coverage of 100% of all exam objectives in this Study Guide means you’ll be ready for: Data Ingestion and Transformation Data Store Management Data Operations and Support Data Security and Governance ABOUT THE AWS DATA ENGINEER – ASSOCIATE CERTIFICATION The AWS Data Engineer – Associate certification validates skills and knowledge in core data-related Amazon Web Services. It recognizes your ability to implement data pipelines and to monitor, troubleshoot, and optimize cost and performance issues in accordance with best practices Interactive learning environment Take your exam prep to the next level with Sybex’s superior interactive online study tools. To access our learning environment, simply visit www.wiley.com/go/sybextestprep, register your book to receive your unique PIN, and instantly gain one year of FREE access after activation to: • Interactive test bank with 5 practice exams to help you identify areas where further review is needed. Get more than 90% of the answers correct, and you’re ready to take the certification exam. • 100 electronic flashcards to reinforce learning and last-minute prep before the exam • Comprehensive glossary in PDF format gives you instant access to the key terms so you are fully prepared
Complete Data Engineering In 8 Hours
DOWNLOAD
Author : QuickTechie | A career growth machine
language : en
Publisher: PappuPass Learning Resources
Release Date : 2025-02-02
Complete Data Engineering In 8 Hours written by QuickTechie | A career growth machine and has been published by PappuPass Learning Resources this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-02 with Computers categories.
"Complete Data Engineering in 8 Hours" is a fast-paced learning guide designed to equip both beginners and experienced professionals with the essential skills required to excel in the field of data engineering. In today's digital age, data is paramount, driving decision-making, automation, and innovation. As QuickTechie.com emphasizes, the role of a Data Engineer is increasingly vital for organizations needing to manage, process, and analyze large volumes of data effectively. This book addresses the growing need for skilled professionals who can navigate the complexities of modern data infrastructure. This book offers a structured approach, providing practical insights into core data engineering concepts. It covers essential areas such as databases, data pipelines, Extract, Transform, Load (ETL) processes, big data technologies, and cloud platforms. Unlike traditional lengthy textbooks, this guide is designed to provide a quick yet comprehensive understanding within a targeted timeframe, allowing readers to quickly grasp fundamental principles and advanced techniques. Readers can expect to follow a step-by-step learning path, mastering the art of designing, building, and scaling data systems efficiently. The book ensures readers gain practical, industry-relevant skills that can be immediately applied in a professional setting. This makes it an excellent resource for those transitioning into the field, those aiming to upskill in their current roles, or individuals preparing for data engineering job interviews. By the end of "Complete Data Engineering in 8 Hours," readers will possess the knowledge and confidence to develop, implement, and optimize data infrastructure. This will empower them to become highly valued assets in the data-driven world, capable of contributing significantly to an organization's data strategies. The book is not just a theoretical guide; it provides hands-on learning opportunities to translate theoretical knowledge into practical skills, aligning with QuickTechie.com commitment to practical, applicable technology learning.