Author: AKASH BALAJI MALI PROF. (DR.) SUDEEPT SINGH YADAV
Publisher: DeepMisti Publication
ISBN: 9360442577
Category : Computers
Languages : en
Pages : 196
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Book Description
In the rapidly evolving world of cloud computing, data engineering plays a pivotal role in building scalable, efficient, and resilient applications. As organizations move their infrastructures to the cloud, the demand for professionals who can design, manage, and optimize data pipelines has surged. "Data Engineering for Cloud Applications: Leveraging Full-Stack Skills for Scalable Solutions" aims to bridge the gap between traditional data engineering practices and the modern demands of cloud-native environments. This book is written for developers, engineers, and architects who want to harness the power of cloud platforms while leveraging their full-stack skills to create scalable, high-performance applications. The integration of cloud technologies such as AWS, Azure, and Google Cloud with data engineering practices enables organizations to manage vast amounts of data effectively, streamline their workflows, and enhance decision-making capabilities. Through practical insights, hands-on examples, and industry best practices, this book guides you through the entire data engineering lifecycle in the cloud, from ingestion to processing and storage. Emphasis is placed on optimizing data flows, reducing latency, and maintaining data integrity across distributed systems. Whether you're working with relational databases, NoSQL systems, or big data solutions, this book offers the tools and techniques necessary to build applications that scale with your business needs. Moreover, this book highlights the synergy between cloud architecture and full-stack development, demonstrating how data engineers can collaborate with front-end and back-end developers to create end-to-end solutions. By the end, you will have a deep understanding of cloud data engineering, allowing you to design robust, scalable solutions that meet the demands of modern businesses in an increasingly data-driven world. Thank you for embarking on this journey with us. Authors
Author: Adi Wijaya
Publisher: Packt Publishing Ltd
ISBN: 1800565062
Category : Computers
Languages : en
Pages : 440
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Book Description
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.
Author: Justin Jenkins
Publisher: BPB Publications
ISBN: 9355518250
Category : Computers
Languages : en
Pages : 433
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Book Description
Unlock a world of job opportunities and accelerate your career growth by mastering MongoDB KEY FEATURES ● Master the fundamental principles of Schema Design, Querying, and Database Administration. ● Explore advanced topics, including Aggregation, Replication, and Sharding. ● Develop a fully functional application utilizing MongoDB Cloud Services. DESCRIPTION MongoDB for Jobseekers serves as the ultimate companion, providing assistance and support throughout your entire MongoDB learning journey. Whether you are an experienced professional exploring new career paths or an aspiring jobseeker looking to enhance your opportunities, this comprehensive guide is specifically designed to cater to your needs. From the basics to advanced concepts, MongoDB for Jobseekers offers a well-structured approach to understanding the intricacies of this powerful NoSQL database. The book then delves into subjects like schema modeling, querying, indexing, and scalability, and discovers the reasons behind MongoDB's widespread popularity. Through clear and practical examples, the book will swiftly help you grasp the fundamental concepts and techniques required to work with MongoDB in real-life scenarios. This extensive guide will not only help establish a strong foundation in MongoDB but also unlock numerous job opportunities. Upon completing this book, you will acquire the necessary confidence and expertise to excel in your job search and embark on a rewarding career path. WHAT YOU WILL LEARN ● Gain a comprehensive understanding of MongoDB's architecture and data model. ● Learn to perform CRUD operations (Create, Read, Update, Delete) in MongoDB. ● Understand indexing strategies for optimizing query performance. ● Discover MongoDB's aggregation framework for complex data analysis. ● Learn about MongoDB's high availability and scalability features. ● Explore integration with programming languages and frameworks. WHO THIS BOOK IS FOR Whether you are a novice starting from scratch or a seasoned professional aiming to enhance your database skills, this book is for individuals who aspire to learn about MongoDB, the contemporary "NoSQL" database. TABLE OF CONTENTS 1. Why MongoDB? 2. MongoDB Jobs and Roles 3. Getting Started 4. A Better Way to Store Data – Documents 5. Let’s Do It – Create, Update and Delete Documents 6. Getting What You Want – Querying 7. Complex Data, Made Simple 8. The MongoDB Aggregation Framework 9. Planning for Performance – Collections and Indexes 10. Getting In and Getting Out – Data Migration 11. Make It Great – Configuration and Monitoring 12. Seamless Scaling – Replication and Sharding 13. Being Proactive – Security and Backups 14. Making Stuff – Programming with MongoDB 15. Tools for Success – MongoDB Shell and Compass UI 16. Cloud Services – MongoDB Atlas 17. MongoDB Atlas – Application Services 18. Jobseeker – Interview Prep 19. Conclusion
Author: Ankur Roy
Publisher: Packt Publishing Ltd
ISBN: 1835081495
Category : Computers
Languages : en
Pages : 220
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Book Description
Unleash DevOps excellence with Python and its ecosystem of tools for seamless orchestration on both local and cloud platforms, such as GCP, AWS, and Azure Key Features Integrate Python into DevOps for streamlined workflows, task automation, and improved collaboration Combine the principles of Python and DevOps into a unified approach for problem solving Learn about Python’s role in Infrastructure as Code (IaC), MLOps, networking, and other domains Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionPython stands out as a powerhouse in DevOps, boasting unparalleled libraries and support, which makes it the preferred programming language for problem solvers worldwide. This book will help you understand the true flexibility of Python, demonstrating how it can be integrated into incredibly useful DevOps workflows and workloads, through practical examples. You'll start by understanding the symbiotic relation between Python and DevOps philosophies and then explore the applications of Python for provisioning and manipulating VMs and other cloud resources to facilitate DevOps activities. With illustrated examples, you’ll become familiar with automating DevOps tasks and learn where and how Python can be used to enhance CI/CD pipelines. Further, the book highlights Python’s role in the Infrastructure as Code (IaC) process development, including its connections with tools like Ansible, SaltStack, and Terraform. The concluding chapters cover advanced concepts such as MLOps, DataOps, and Python’s integration with generative AI, offering a glimpse into the areas of monitoring, logging, Kubernetes, and more. By the end of this book, you’ll know how to leverage Python in your DevOps-based workloads to make your life easier and save time.What you will learn Implement DevOps practices and principles using Python Enhance your DevOps workloads with Python Create Python-based DevOps solutions to improve your workload efficiency Understand DevOps objectives and the mindset needed to achieve them Use Python to automate DevOps tasks and increase productivity Explore the concepts of DevSecOps, MLOps, DataOps, and more Use Python for containerized workloads in Docker and Kubernetes Who this book is for This book is for IT professionals venturing into DevOps, particularly programmers seeking to apply their existing programming knowledge to excel in this field. For DevOps professionals without a coding background, this book serves as a resource to enhance their understanding of development practices and communicate more effectively with developers. Solutions architects, programmers, and anyone regularly working with DevOps solutions and Python will also benefit from this hands-on guide.
Author: Dan Sullivan
Publisher: John Wiley & Sons
ISBN: 1119618452
Category : Computers
Languages : en
Pages : 357
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Book Description
The proven Study Guide that prepares you for this new Google Cloud exam The Google Cloud Certified Professional Data Engineer Study Guide, provides everything you need to prepare for this important exam and master the skills necessary to land that coveted Google Cloud Professional Data Engineer certification. Beginning with a pre-book assessment quiz to evaluate what you know before you begin, each chapter features exam objectives and review questions, plus the online learning environment includes additional complete practice tests. Written by Dan Sullivan, a popular and experienced online course author for machine learning, big data, and Cloud topics, Google Cloud Certified Professional Data Engineer Study Guide is your ace in the hole for deploying and managing analytics and machine learning applications. Build and operationalize storage systems, pipelines, and compute infrastructure Understand machine learning models and learn how to select pre-built models Monitor and troubleshoot machine learning models Design analytics and machine learning applications that are secure, scalable, and highly available. This exam guide is designed to help you develop an in depth understanding of data engineering and machine learning on Google Cloud Platform.
Author: Russell Jurney
Publisher: "O'Reilly Media, Inc."
ISBN: 1491960086
Category : Computers
Languages : en
Pages : 351
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Book Description
Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll learn an iterative approach that lets you quickly change the kind of analysis you’re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization. Build value from your data in a series of agile sprints, using the data-value pyramid Extract features for statistical models from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future via classification and regression Translate predictions into actions Get feedback from users after each sprint to keep your project on track
Author: Rajkumar Buyya
Publisher: John Wiley & Sons
ISBN: 1118002202
Category : Computers
Languages : en
Pages : 607
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Book Description
The primary purpose of this book is to capture the state-of-the-art in Cloud Computing technologies and applications. The book will also aim to identify potential research directions and technologies that will facilitate creation a global market-place of cloud computing services supporting scientific, industrial, business, and consumer applications. We expect the book to serve as a reference for larger audience such as systems architects, practitioners, developers, new researchers and graduate level students. This area of research is relatively recent, and as such has no existing reference book that addresses it. This book will be a timely contribution to a field that is gaining considerable research interest, momentum, and is expected to be of increasing interest to commercial developers. The book is targeted for professional computer science developers and graduate students especially at Masters level. As Cloud Computing is recognized as one of the top five emerging technologies that will have a major impact on the quality of science and society over the next 20 years, its knowledge will help position our readers at the forefront of the field.
Author: Russell Jurney
Publisher: "O'Reilly Media, Inc."
ISBN: 1449326919
Category : Computers
Languages : en
Pages : 269
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Book Description
Mining big data requires a deep investment in people and time. How can you be sure you’re building the right models? With this hands-on book, you’ll learn a flexible toolset and methodology for building effective analytics applications with Hadoop. Using lightweight tools such as Python, Apache Pig, and the D3.js library, your team will create an agile environment for exploring data, starting with an example application to mine your own email inboxes. You’ll learn an iterative approach that enables you to quickly change the kind of analysis you’re doing, depending on what the data is telling you. All example code in this book is available as working Heroku apps. Create analytics applications by using the agile big data development methodology Build value from your data in a series of agile sprints, using the data-value stack Gain insight by using several data structures to extract multiple features from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future, and translate predictions into action Get feedback from users after each sprint to keep your project on track
Author: Nayyar Dr. Anand
Publisher: BPB Publications
ISBN: 9388511506
Category : Computers
Languages : en
Pages : 428
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Book Description
Great POSSIBILITIES and high future prospects to become ten times folds in the near FUTUREKey features Comprehensively gives clear picture of current state-of-the-art aspect of cloud computing by elaborating terminologies, models and other related terms. Enlightens all major players in Cloud Computing industry providing services in terms of SaaS, PaaS and IaaS. Highlights Cloud Computing Simulators, Security Aspect and Resource Allocation. In-depth presentation with well-illustrated diagrams and simple to understand technical concepts of cloud. Description The book "e;Handbook of Cloud Computing"e; provides the latest and in-depth information of this relatively new and another platform for scientific computing which has great possibilities and high future prospects to become ten folds in near future. The book covers in comprehensive manner all aspects and terminologies associated with cloud computing like SaaS, PaaS and IaaS and also elaborates almost every cloud computing service model.The book highlights several other aspects of cloud computing like Security, Resource allocation, Simulation Platforms and futuristic trend i.e. Mobile cloud computing. The book will benefit all the readers with all in-depth technical information which is required to understand current and futuristic concepts of cloud computing. No prior knowledge of cloud computing or any of its related technology is required in reading this book. What will you learn Cloud Computing, Virtualisation Software as a Service, Platform as a Service, Infrastructure as a Service Data in Cloud and its Security Cloud Computing - Simulation, Mobile Cloud Computing Specific Cloud Service Models Resource Allocation in Cloud Computing Who this book is for Students of Polytechnic Diploma Classes- Computer Science/ Information Technology Graduate Students- Computer Science/ CSE / IT/ Computer Applications Master Class Students-Msc (CS/IT)/ MCA/ M.Phil, M.Tech, M.S. Researcher's-Ph.D Research Scholars doing work in Virtualization, Cloud Computing and Cloud Security Industry Professionals- Preparing for Certifications, Implementing Cloud Computing and even working on Cloud Security Table of contents1. Introduction to Cloud Computing2. Virtualisation3. Software as a Service4. Platform as a Service5. Infrastructure as a Service6. Data in Cloud7. Cloud Security 8. Cloud Computing - Simulation9. Specific Cloud Service Models10. Resource Allocation in Cloud Computing11. Mobile Cloud Computing About the authorDr. Anand Nayyar received Ph.D (Computer Science) in Wireless Sensor Networks and Swarm Intelligence. Presently he is working in Graduate School, Duy Tan University, Da Nang, Vietnam. He has total of fourteen Years of Teaching, Research and Consultancy experience with more than 250 Research Papers in various International Conferences and highly reputed journals. He is certified Professional with more than 75 certificates and member of 50 Professional Organizations. He is acting as "e;ACM DISTINGUISHED SPEAKER"e;
Author: Kai Hwang
Publisher: Morgan Kaufmann
ISBN: 0128002042
Category : Computers
Languages : en
Pages : 671
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Book Description
Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. It is the first modern, up-to-date distributed systems textbook; it explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems. Topics covered by this book include: facilitating management, debugging, migration, and disaster recovery through virtualization; clustered systems for research or ecommerce applications; designing systems as web services; and social networking systems using peer-to-peer computing. The principles of cloud computing are discussed using examples from open-source and commercial applications, along with case studies from the leading distributed computing vendors such as Amazon, Microsoft, and Google. Each chapter includes exercises and further reading, with lecture slides and more available online. This book will be ideal for students taking a distributed systems or distributed computing class, as well as for professional system designers and engineers looking for a reference to the latest distributed technologies including cloud, P2P and grid computing. - Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing - Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more - Explains how to use virtualization to facilitate management, debugging, migration, and disaster recovery - Designed for undergraduate or graduate students taking a distributed systems course—each chapter includes exercises and further reading, with lecture slides and more available online
