Download or read book Serverless Machine Learning with Amazon Redshift ML written by Debu Panda and published by Packt Publishing Ltd. This book was released on 2023-08-30 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supercharge and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale Key Features Leverage supervised learning to build binary classification, multi-class classification, and regression models Learn to use unsupervised learning using the K-means clustering method Master the art of time series forecasting using Redshift ML Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAmazon Redshift Serverless enables organizations to run petabyte-scale cloud data warehouses quickly and in a cost-effective way, enabling data science professionals to efficiently deploy cloud data warehouses and leverage easy-to-use tools to train models and run predictions. This practical guide will help developers and data professionals working with Amazon Redshift data warehouses to put their SQL knowledge to work for training and deploying machine learning models. The book begins by helping you to explore the inner workings of Redshift Serverless as well as the foundations of data analytics and types of data machine learning. With the help of step-by-step explanations of essential concepts and practical examples, you’ll then learn to build your own classification and regression models. As you advance, you’ll find out how to deploy various types of machine learning projects using familiar SQL code, before delving into Redshift ML. In the concluding chapters, you’ll discover best practices for implementing serverless architecture with Redshift. By the end of this book, you’ll be able to configure and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale.What you will learn Utilize Redshift Serverless for data ingestion, data analysis, and machine learning Create supervised and unsupervised models and learn how to supply your own custom parameters Discover how to use time series forecasting in your data warehouse Create a SageMaker endpoint and use that to build a Redshift ML model for remote inference Find out how to operationalize machine learning in your data warehouse Use model explainability and calculate probabilities with Amazon Redshift ML Who this book is forData scientists and machine learning developers working with Amazon Redshift who want to explore its machine-learning capabilities will find this definitive guide helpful. A basic understanding of machine learning techniques and working knowledge of Amazon Redshift is needed to make the most of this book.

Download or read book Serverless Machine Learning with Amazon Redshift ML written by Debu Panda and published by Packt Publishing Ltd. This book was released on 2023-08-30 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supercharge and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale Key Features Leverage supervised learning to build binary classification, multi-class classification, and regression models Learn to use unsupervised learning using the K-means clustering method Master the art of time series forecasting using Redshift ML Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAmazon Redshift Serverless enables organizations to run petabyte-scale cloud data warehouses quickly and in a cost-effective way, enabling data science professionals to efficiently deploy cloud data warehouses and leverage easy-to-use tools to train models and run predictions. This practical guide will help developers and data professionals working with Amazon Redshift data warehouses to put their SQL knowledge to work for training and deploying machine learning models. The book begins by helping you to explore the inner workings of Redshift Serverless as well as the foundations of data analytics and types of data machine learning. With the help of step-by-step explanations of essential concepts and practical examples, you’ll then learn to build your own classification and regression models. As you advance, you’ll find out how to deploy various types of machine learning projects using familiar SQL code, before delving into Redshift ML. In the concluding chapters, you’ll discover best practices for implementing serverless architecture with Redshift. By the end of this book, you’ll be able to configure and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale.What you will learn Utilize Redshift Serverless for data ingestion, data analysis, and machine learning Create supervised and unsupervised models and learn how to supply your own custom parameters Discover how to use time series forecasting in your data warehouse Create a SageMaker endpoint and use that to build a Redshift ML model for remote inference Find out how to operationalize machine learning in your data warehouse Use model explainability and calculate probabilities with Amazon Redshift ML Who this book is forData scientists and machine learning developers working with Amazon Redshift who want to explore its machine-learning capabilities will find this definitive guide helpful. A basic understanding of machine learning techniques and working knowledge of Amazon Redshift is needed to make the most of this book.

Download or read book Amazon Redshift The Definitive Guide written by Rajesh Francis and published by "O'Reilly Media, Inc.". This book was released on 2023-10-03 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: Amazon Redshift powers analytic cloud data warehouses worldwide, from startups to some of the largest enterprise data warehouses available today. This practical guide thoroughly examines this managed service and demonstrates how you can use it to extract value from your data immediately, rather than go through the heavy lifting required to run a typical data warehouse. Analytic specialists Rajesh Francis, Rajiv Gupta, and Milind Oke detail Amazon Redshift's underlying mechanisms and options to help you explore out-of-the box automation. Whether you're a data engineer who wants to learn the art of the possible or a DBA looking to take advantage of machine learning-based auto-tuning, this book helps you get the most value from Amazon Redshift. By understanding Amazon Redshift features, you'll achieve excellent analytic performance at the best price, with the least effort. This book helps you: Build a cloud data strategy around Amazon Redshift as foundational data warehouse Get started with Amazon Redshift with simple-to-use data models and design best practices Understand how and when to use Redshift Serverless and Redshift provisioned clusters Take advantage of auto-tuning options inherent in Amazon Redshift and understand manual tuning options Transform your data platform for predictive analytics using Redshift ML and break silos using data sharing Learn best practices for security, monitoring, resilience, and disaster recovery Leverage Amazon Redshift integration with other AWS services to unlock additional value

Download or read book MLOps with Red Hat OpenShift written by Ross Brigoli and published by Packt Publishing Ltd. This book was released on 2024-01-31 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build and manage MLOps pipelines with this practical guide to using Red Hat OpenShift Data Science, unleashing the power of machine learning workflows Key Features Grasp MLOps and machine learning project lifecycle through concept introductions Get hands on with provisioning and configuring Red Hat OpenShift Data Science Explore model training, deployment, and MLOps pipeline building with step-by-step instructions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMLOps with OpenShift offers practical insights for implementing MLOps workflows on the dynamic OpenShift platform. As organizations worldwide seek to harness the power of machine learning operations, this book lays the foundation for your MLOps success. Starting with an exploration of key MLOps concepts, including data preparation, model training, and deployment, you’ll prepare to unleash OpenShift capabilities, kicking off with a primer on containers, pods, operators, and more. With the groundwork in place, you’ll be guided to MLOps workflows, uncovering the applications of popular machine learning frameworks for training and testing models on the platform. As you advance through the chapters, you’ll focus on the open-source data science and machine learning platform, Red Hat OpenShift Data Science, and its partner components, such as Pachyderm and Intel OpenVino, to understand their role in building and managing data pipelines, as well as deploying and monitoring machine learning models. Armed with this comprehensive knowledge, you’ll be able to implement MLOps workflows on the OpenShift platform proficiently.What you will learn Build a solid foundation in key MLOps concepts and best practices Explore MLOps workflows, covering model development and training Implement complete MLOps workflows on the Red Hat OpenShift platform Build MLOps pipelines for automating model training and deployments Discover model serving approaches using Seldon and Intel OpenVino Get to grips with operating data science and machine learning workloads in OpenShift Who this book is for This book is for MLOps and DevOps engineers, data architects, and data scientists interested in learning the OpenShift platform. Particularly, developers who want to learn MLOps and its components will find this book useful. Whether you’re a machine learning engineer or software developer, this book serves as an essential guide to building scalable and efficient machine learning workflows on the OpenShift platform.

Download or read book Machine Learning Engineering on AWS written by Joshua Arvin Lat and published by Packt Publishing Ltd. This book was released on 2022-10-27 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work seamlessly with production-ready machine learning systems and pipelines on AWS by addressing key pain points encountered in the ML life cycle Key FeaturesGain practical knowledge of managing ML workloads on AWS using Amazon SageMaker, Amazon EKS, and moreUse container and serverless services to solve a variety of ML engineering requirementsDesign, build, and secure automated MLOps pipelines and workflows on AWSBook Description There is a growing need for professionals with experience in working on machine learning (ML) engineering requirements as well as those with knowledge of automating complex MLOps pipelines in the cloud. This book explores a variety of AWS services, such as Amazon Elastic Kubernetes Service, AWS Glue, AWS Lambda, Amazon Redshift, and AWS Lake Formation, which ML practitioners can leverage to meet various data engineering and ML engineering requirements in production. This machine learning book covers the essential concepts as well as step-by-step instructions that are designed to help you get a solid understanding of how to manage and secure ML workloads in the cloud. As you progress through the chapters, you'll discover how to use several container and serverless solutions when training and deploying TensorFlow and PyTorch deep learning models on AWS. You'll also delve into proven cost optimization techniques as well as data privacy and model privacy preservation strategies in detail as you explore best practices when using each AWS. By the end of this AWS book, you'll be able to build, scale, and secure your own ML systems and pipelines, which will give you the experience and confidence needed to architect custom solutions using a variety of AWS services for ML engineering requirements. What you will learnFind out how to train and deploy TensorFlow and PyTorch models on AWSUse containers and serverless services for ML engineering requirementsDiscover how to set up a serverless data warehouse and data lake on AWSBuild automated end-to-end MLOps pipelines using a variety of servicesUse AWS Glue DataBrew and SageMaker Data Wrangler for data engineeringExplore different solutions for deploying deep learning models on AWSApply cost optimization techniques to ML environments and systemsPreserve data privacy and model privacy using a variety of techniquesWho this book is for This book is for machine learning engineers, data scientists, and AWS cloud engineers interested in working on production data engineering, machine learning engineering, and MLOps requirements using a variety of AWS services such as Amazon EC2, Amazon Elastic Kubernetes Service (EKS), Amazon SageMaker, AWS Glue, Amazon Redshift, AWS Lake Formation, and AWS Lambda -- all you need is an AWS account to get started. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.

Download or read book Applied Machine Learning and High Performance Computing on AWS written by Mani Khanuja and published by Packt Publishing Ltd. This book was released on 2022-12-30 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build, train, and deploy large machine learning models at scale in various domains such as computational fluid dynamics, genomics, autonomous vehicles, and numerical optimization using Amazon SageMaker Key FeaturesUnderstand the need for high-performance computing (HPC)Build, train, and deploy large ML models with billions of parameters using Amazon SageMakerLearn best practices and architectures for implementing ML at scale using HPCBook Description Machine learning (ML) and high-performance computing (HPC) on AWS run compute-intensive workloads across industries and emerging applications. Its use cases can be linked to various verticals, such as computational fluid dynamics (CFD), genomics, and autonomous vehicles. This book provides end-to-end guidance, starting with HPC concepts for storage and networking. It then progresses to working examples on how to process large datasets using SageMaker Studio and EMR. Next, you'll learn how to build, train, and deploy large models using distributed training. Later chapters also guide you through deploying models to edge devices using SageMaker and IoT Greengrass, and performance optimization of ML models, for low latency use cases. By the end of this book, you'll be able to build, train, and deploy your own large-scale ML application, using HPC on AWS, following industry best practices and addressing the key pain points encountered in the application life cycle. What you will learnExplore data management, storage, and fast networking for HPC applicationsFocus on the analysis and visualization of a large volume of data using SparkTrain visual transformer models using SageMaker distributed trainingDeploy and manage ML models at scale on the cloud and at the edgeGet to grips with performance optimization of ML models for low latency workloadsApply HPC to industry domains such as CFD, genomics, AV, and optimizationWho this book is for The book begins with HPC concepts, however, it expects you to have prior machine learning knowledge. This book is for ML engineers and data scientists interested in learning advanced topics on using large datasets for training large models using distributed training concepts on AWS, deploying models at scale, and performance optimization for low latency use cases. Practitioners in fields such as numerical optimization, computation fluid dynamics, autonomous vehicles, and genomics, who require HPC for applying ML models to applications at scale will also find the book useful.

Download or read book Serverless Machine Learning with Amazon Redshift ML written by Debu Panda and published by . This book was released on 2023-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book helps you implement end-to-end serverless architectures for ingestion, analytics, and machine learning using Redshift Serverless and Redshift ML.

Download or read book AWS Certified SysOps Administrator Associate SOA C01 Cert Guide written by Anthony J. Sequeira and published by Pearson IT Certification. This book was released on 2019-11-26 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the eBook version of the print title. Note that the eBook does not provide access to the practice test software that accompanies the print book. Learn, prepare, and practice for AWS Certified SysOps Administrator Associate (SOA-C01) exam success with this Cert Guide from Pearson IT Certification, a leader in IT Certification learning. Master AWS Certified SysOps Administrator Associate (SOA-C01) exam topics Assess your knowledge with chapter-ending quizzes Review key concepts with exam preparation tasks AWS Certified SysOps Administrator Associate (SOA-C01) Cert Guide is a best-of-breed exam study guide. Best-selling author and expert instructor Anthony Sequeira shares preparation hints and test-taking tips, helping you identify areas of weakness and improve both your conceptual knowledge and hands-on skills. Material is presented in a concise manner, focusing on increasing your understanding and retention of exam topics. The book presents you with an organized test preparation routine through the use of proven series elements and techniques. Exam topic lists make referencing easy. Chapter-ending Exam Preparation Tasks help you drill on key concepts you must know thoroughly. Review questions help you assess your knowledge, and a final preparation chapter guides you through tools and resources to help you craft your final study plan. Well-regarded for its level of detail, assessment features, and challenging review questions and exercises, this study guide helps you master the concepts and techniques that will enable you to succeed on the exam the first time. The study guide helps you master all the topics on the AWS Certified SysOps Administrator Associate exam, including: Monitoring and reporting: create and maintain metrics and alarms; recognize, differentiate, and remediate based on metrics High availability: implement scalability and elasticity; recognize and differentiate highly available and resilient AWS environments Deployment and provisioning: provision cloud resources, and identify and remediate deployment issues Storage and data management: create and manage data retention; identify and implement data protection, encryption, and capacity planning Security and compliance: implement and manage security policies; implement access controls; understand the shared responsibility model Networking: use AWS networking features and connectivity services; gather and interpret relevant data for network troubleshooting Automation and optimization: manage and assess resource utilization, use cost-optimization strategies, and automate processes

Download or read book Machine Learning with LightGBM and Python written by Andrich van Wyk and published by Packt Publishing Ltd. This book was released on 2023-09-29 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take your software to the next level and solve real-world data science problems by building production-ready machine learning solutions using LightGBM and Python Key Features Get started with LightGBM, a powerful gradient-boosting library for building ML solutions Apply data science processes to real-world problems through case studies Elevate your software by building machine learning solutions on scalable platforms Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMachine Learning with LightGBM and Python is a comprehensive guide to learning the basics of machine learning and progressing to building scalable machine learning systems that are ready for release. This book will get you acquainted with the high-performance gradient-boosting LightGBM framework and show you how it can be used to solve various machine-learning problems to produce highly accurate, robust, and predictive solutions. Starting with simple machine learning models in scikit-learn, you’ll explore the intricacies of gradient boosting machines and LightGBM. You’ll be guided through various case studies to better understand the data science processes and learn how to practically apply your skills to real-world problems. As you progress, you’ll elevate your software engineering skills by learning how to build and integrate scalable machine-learning pipelines to process data, train models, and deploy them to serve secure APIs using Python tools such as FastAPI. By the end of this book, you’ll be well equipped to use various -of-the-art tools that will help you build production-ready systems, including FLAML for AutoML, PostgresML for operating ML pipelines using Postgres, high-performance distributed training and serving via Dask, and creating and running models in the Cloud with AWS Sagemaker.What you will learn Get an overview of ML and working with data and models in Python using scikit-learn Explore decision trees, ensemble learning, gradient boosting, DART, and GOSS Master LightGBM and apply it to classification and regression problems Tune and train your models using AutoML with FLAML and Optuna Build ML pipelines in Python to train and deploy models with secure and performant APIs Scale your solutions to production readiness with AWS Sagemaker, PostgresML, and Dask Who this book is forThis book is for software engineers aspiring to be better machine learning engineers and data scientists unfamiliar with LightGBM, looking to gain in-depth knowledge of its libraries. Basic to intermediate Python programming knowledge is required to get started with the book. The book is also an excellent source for ML veterans, with a strong focus on ML engineering with up-to-date and thorough coverage of platforms such as AWS Sagemaker, PostgresML, and Dask.

Download or read book AWS certification guide AWS Certified DevOps Engineer Professional written by Cybellium Ltd and published by Cybellium Ltd. This book was released on with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: AWS Certification Guide - AWS Certified DevOps Engineer – Professional Master the Art of AWS DevOps at a Professional Level Embark on a comprehensive journey to mastering DevOps practices in the AWS ecosystem with this definitive guide for the AWS Certified DevOps Engineer – Professional certification. Tailored for DevOps professionals aiming to validate their expertise, this book is an invaluable resource for mastering the blend of operations and development on AWS. Within These Pages, You'll Discover: Advanced DevOps Techniques: Deep dive into the advanced practices of AWS DevOps, from infrastructure as code to automated scaling and management. Comprehensive Coverage of AWS Services: Explore the full range of AWS services relevant to DevOps, including their integration and optimization for efficient workflows. Practical, Real-World Scenarios: Engage with detailed case studies and practical examples that demonstrate effective DevOps strategies in action on AWS. Focused Exam Preparation: Get a thorough understanding of the exam structure, with in-depth chapters aligned with each domain of the certification exam, complemented by targeted practice questions. Written by a DevOps Veteran Authored by an experienced AWS DevOps Engineer, this guide marries practical field expertise with a deep understanding of AWS services, offering readers insider insights and proven strategies. Your Comprehensive Guide to DevOps Certification Whether you’re an experienced DevOps professional or looking to take your skills to the next level, this book is your comprehensive companion, guiding you through the complexities of AWS DevOps and preparing you for the Professional certification exam. Elevate Your DevOps Skills Go beyond the basics and gain a profound, practical understanding of DevOps practices in the AWS environment. This guide is more than a certification prep book; it's a blueprint for excelling in AWS DevOps at a professional level. Begin Your Advanced DevOps Journey Embark on your path to becoming a certified AWS DevOps Engineer – Professional. With this guide, you're not just preparing for an exam; you're advancing your career in the fast-evolving field of AWS DevOps. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Download or read book AWS Certified AI Machine Learning Specialist written by and published by Cybellium . This book was released on with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com

Download or read book Serverless Programming Cookbook written by Heartin Kanikathottu and published by Packt Publishing Ltd. This book was released on 2019-01-31 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build, secure, and deploy real-world serverless applications in AWS and peek into the serverless cloud offerings from Azure, Google Cloud, and IBM Cloud Key FeaturesBuild serverless applications with AWS Lambda, AWS CloudFormation and AWS CloudWatchPerform data analytics and natural language processing(NLP)on the AWS serverless platformExplore various design patterns and best practices involved in serverless computingBook Description Managing physical servers will be a thing of the past once you’re able to harness the power of serverless computing. If you’re already prepped with the basics of serverless computing, Serverless Programming Cookbook will help you take the next step ahead. This recipe-based guide provides solutions to problems you might face while building serverless applications. You'll begin by setting up Amazon Web Services (AWS), the primary cloud provider used for most recipes. The next set of recipes will cover various components to build a Serverless application including REST APIs, database, user management, authentication, web hosting, domain registration, DNS management, CDN, messaging, notifications and monitoring. The book also introduces you to the latest technology trends such as Data Streams, Machine Learning and NLP. You will also see patterns and practices for using various services in a real world application. Finally, to broaden your understanding of Serverless computing, you'll also cover getting started guides for other cloud providers such as Azure, Google Cloud Platform and IBM cloud. By the end of this book, you’ll have acquired the skills you need to build serverless applications efficiently using various cloud offerings. What you will learnServerless computing in AWS and explore services with other cloudsDevelop full-stack apps with API Gateway, Cognito, Lambda and DynamoDBWeb hosting with S3, CloudFront, Route 53 and AWS Certificate ManagerSQS and SNS for effective communication between microservices Monitoring and troubleshooting with CloudWatch logs and metrics Explore Kinesis Streams, Amazon ML models and Alexa Skills KitWho this book is for For developers looking for practical solutions to common problems while building a serverless application, this book provides helpful recipes. To get started with this intermediate-level book, knowledge of basic programming is a must.

Download or read book AWS certification guide AWS Certified SysOps Administrator Associate written by Cybellium Ltd and published by Cybellium Ltd. This book was released on with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: AWS Certification Guide - AWS Certified SysOps Administrator – Associate Forge Your Path in AWS System Operations Embark on a comprehensive journey to mastering AWS system operations with this definitive guide. Designed for individuals aiming to become AWS Certified SysOps Administrators – Associate, this book is a treasure trove of knowledge, offering deep insights into the world of AWS from a SysOps perspective. What’s Inside: Fundamental to Advanced Concepts: From basic AWS services to advanced operational techniques, this guide covers all aspects necessary for SysOps mastery. Real-World Scenarios: Engage with practical examples and case studies that bring theory to life, demonstrating how AWS is managed and optimized in a real-world setting. Examination Blueprint: Detailed breakdown of the exam structure, ensuring you are well-prepared for every topic and question type you will encounter. Practice Makes Perfect: Challenge yourself with practice questions and mock exams designed to reflect the actual certification test, enhancing your readiness and confidence. Crafted by an AWS SysOps Expert This guide is written by an experienced AWS SysOps Administrator, combining practical field knowledge with educational expertise to provide you with an unparalleled learning experience. Your Comprehensive SysOps Resource Whether you're new to AWS system operations or looking to formalize your skills with certification, this book is your essential companion, guiding you through the complexities of AWS and preparing you for the SysOps Administrator – Associate exam. Elevate Your AWS SysOps Skills This guide is more than just a preparation tool for the exam; it's a roadmap for building a successful career in AWS system operations, equipping you with the skills and knowledge to excel in this dynamic field. Begin Your AWS SysOps Administrator Journey Step into the role of an AWS SysOps Administrator with confidence and expertise. This guide is your first step towards achieving certification and advancing your career in the thriving world of AWS. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Download or read book Serverless ETL and Analytics with AWS Glue written by Vishal Pathak and published by Packt Publishing Ltd. This book was released on 2022-08-30 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build efficient data lakes that can scale to virtually unlimited size using AWS Glue Key Features Book DescriptionOrganizations these days have gravitated toward services such as AWS Glue that undertake undifferentiated heavy lifting and provide serverless Spark, enabling you to create and manage data lakes in a serverless fashion. This guide shows you how AWS Glue can be used to solve real-world problems along with helping you learn about data processing, data integration, and building data lakes. Beginning with AWS Glue basics, this book teaches you how to perform various aspects of data analysis such as ad hoc queries, data visualization, and real-time analysis using this service. It also provides a walk-through of CI/CD for AWS Glue and how to shift left on quality using automated regression tests. You’ll find out how data security aspects such as access control, encryption, auditing, and networking are implemented, as well as getting to grips with useful techniques such as picking the right file format, compression, partitioning, and bucketing. As you advance, you’ll discover AWS Glue features such as crawlers, Lake Formation, governed tables, lineage, DataBrew, Glue Studio, and custom connectors. The concluding chapters help you to understand various performance tuning, troubleshooting, and monitoring options. By the end of this AWS book, you’ll be able to create, manage, troubleshoot, and deploy ETL pipelines using AWS Glue.What you will learn Apply various AWS Glue features to manage and create data lakes Use Glue DataBrew and Glue Studio for data preparation Optimize data layout in cloud storage to accelerate analytics workloads Manage metadata including database, table, and schema definitions Secure your data during access control, encryption, auditing, and networking Monitor AWS Glue jobs to detect delays and loss of data Integrate Spark ML and SageMaker with AWS Glue to create machine learning models Who this book is for ETL developers, data engineers, and data analysts

Download or read book Mastering Data Ingestion written by Cybellium Ltd and published by Cybellium Ltd. This book was released on with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficiently Capture and Prepare Data for Analysis Are you ready to optimize the way your organization captures and prepares data for analysis? "Mastering Data Ingestion" is your definitive guide to mastering the art of efficiently collecting, transforming, and organizing data for insights. Whether you're a data engineer streamlining data pipelines or a business leader aiming to leverage accurate information, this book equips you with the knowledge and strategies to excel in data ingestion. Key Features: 1. Enter the World of Data Ingestion: Immerse yourself in the realm of data ingestion, understanding its significance, challenges, and opportunities. Build a strong foundation that empowers you to design seamless processes for data collection. 2. Data Collection Techniques: Master various data collection techniques. Learn about batch processing, real-time streaming, and event-driven approaches for ingesting data from diverse sources. 3. Data Transformation and Enrichment: Delve into data transformation and enrichment during ingestion. Explore techniques for cleansing, structuring, and augmenting data to ensure its quality and usability. 4. Ingestion Patterns and Architectures: Uncover the power of data ingestion patterns and architectures. Learn how to design scalable and fault-tolerant data pipelines that handle high volumes of information. 5. Data Formats and Serialization: Explore data formats and serialization techniques. Learn how to handle diverse data structures, choose appropriate serialization methods, and ensure interoperability. 6. Ingestion Tools and Platforms: Discover a range of tools and platforms for data ingestion. Explore ETL (Extract, Transform, Load) tools, message brokers, and cloud-based services for efficient data movement. 7. Real-Time Data Ingestion: Master real-time data ingestion techniques. Learn how to capture and process streaming data for instant insights and timely decision-making. 8. Data Ingestion Best Practices: Delve into best practices for successful data ingestion projects. Learn how to handle data schema evolution, ensure data integrity, and optimize performance. 9. Cloud Data Ingestion: Explore cloud-based data ingestion strategies. Learn how to ingest data from cloud services, integrate with cloud databases, and leverage serverless architectures. 10. Real-World Applications: Gain insights into real-world use cases of data ingestion across industries. From IoT data streams to social media feeds, discover how organizations leverage efficient data collection for competitive advantage. Who This Book Is For: "Mastering Data Ingestion" is an essential resource for data engineers, analysts, and business professionals aiming to excel in efficiently collecting and preparing data for analysis. Whether you're enhancing your technical skills or optimizing data workflows, this book will guide you through the intricacies and empower you to harness the full potential of data ingestion. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Download or read book AWS Certified Data Analytics Study Guide with Online Labs written by Asif Abbasi and published by John Wiley & Sons. This book was released on 2021-04-13 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Virtual, hands-on learning labs allow you to apply your technical skills in realistic environments. So Sybex has bundled AWS labs from XtremeLabs with our popular AWS Certified Data Analytics Study Guide to give you the same experience working in these labs as you prepare for the Certified Data Analytics Exam that you would face in a real-life application. These labs in addition to the book are a proven way to prepare for the certification and for work as an AWS Data Analyst. AWS Certified Data Analytics Study Guide: Specialty (DAS-C01) Exam is intended for individuals who perform in a data analytics-focused role. This UPDATED exam validates an examinee's comprehensive understanding of using AWS services to design, build, secure, and maintain analytics solutions that provide insight from data. It assesses an examinee's ability to define AWS data analytics services and understand how they integrate with each other; and explain how AWS data analytics services fit in the data lifecycle of collection, storage, processing, and visualization. The book focuses on the following domains: • Collection • Storage and Data Management • Processing • Analysis and Visualization • Data Security This is your opportunity to take the next step in your career by expanding and validating your skills on the AWS cloud. AWS is the frontrunner in cloud computing products and services, and the AWS Certified Data Analytics Study Guide: Specialty exam will get you fully prepared through expert content, and real-world knowledge, key exam essentials, chapter review questions, and much more. Written by an AWS subject-matter expert, this study guide covers exam concepts, and provides key review on exam topics. Readers will also have access to Sybex's superior online interactive learning environment and test bank, including chapter tests, practice exams, a glossary of key terms, and electronic flashcards. And included with this version of the book, XtremeLabs virtual labs that run from your browser. The registration code is included with the book and gives you 6 months of unlimited access to XtremeLabs AWS Certified Data Analytics Labs with 3 unique lab modules based on the book.

Download or read book AWS Certified Enterprise IT Engineer written by and published by Cybellium . This book was released on with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com