Author: Stefan Bauer
Publisher: Packt Publishing Ltd
Release Date: 2013-06-14
Genre: Business & Economics
Getting Started With Amazon Redshift is a step-by-step, practical guide to the world of Redshift. Learn to load, manage, and query data on Redshift.This book is for CIOs, enterprise architects, developers, and anyone else who needs to get familiar with RedShift. The CIO will gain an understanding of what their technical staff is working on; the technical implementation personnel will get an in-depth view of the technology, and what it will take to implement their own solutions.
Learn to leverage Amazon's powerful platform for your predictive analytics needs About This Book Create great machine learning models that combine the power of algorithms with interactive tools without worrying about the underlying complexity Learn the What's next? of machine learning—machine learning on the cloud—with this unique guide Create web services that allow you to perform affordable and fast machine learning on the cloud Who This Book Is For This book is intended for data scientists and managers of predictive analytics projects; it will teach beginner- to advanced-level machine learning practitioners how to leverage Amazon Machine Learning and complement their existing Data Science toolbox. No substantive prior knowledge of Machine Learning, Data Science, statistics, or coding is required. What You Will Learn Learn how to use the Amazon Machine Learning service from scratch for predictive analytics Gain hands-on experience of key Data Science concepts Solve classic regression and classification problems Run projects programmatically via the command line and the Python SDK Leverage the Amazon Web Service ecosystem to access extended data sources Implement streaming and advanced projects In Detail Predictive analytics is a complex domain requiring coding skills, an understanding of the mathematical concepts underpinning machine learning algorithms, and the ability to create compelling data visualizations. Following AWS simplifying Machine learning, this book will help you bring predictive analytics projects to fruition in three easy steps: data preparation, model tuning, and model selection. This book will introduce you to the Amazon Machine Learning platform and will implement core data science concepts such as classification, regression, regularization, overfitting, model selection, and evaluation. Furthermore, you will learn to leverage the Amazon Web Service (AWS) ecosystem for extended access to data sources, implement realtime predictions, and run Amazon Machine Learning projects via the command line and the Python SDK. Towards the end of the book, you will also learn how to apply these services to other problems, such as text mining, and to more complex datasets. Style and approach This book will include use cases you can relate to. In a very practical manner, you will explore the various capabilities of Amazon Machine Learning services, allowing you to implementing them in your environment with consummate ease.
This book is a practical guide to developing, administering, and managing applications and infrastructures with AWS. With this, you'll be able to create, design, and manage an entire application life cycle on AWS by using the AWS SDKs, APIs, and the AWS Management Console. You'll start with the basics of the AWS development platform and look into creating stable and scalable infrastructures using EC2, EBS, and Elastic Load Balancers. You'll then deep-dive into designing and developing your own web app and learn about the alarm mechanism, disaster recovery plan, and connecting AWS services through REST-based APIs. Following this, you'll get to grips with CloudFormation, auto scaling, bootstrap AWS EC2 instances, automation and deployment with Chef, and develop your knowledge of big data and Apache Hadoop on AWS Cloud. At the end, you'll have learned about AWS billing, cost-control architecture designs, AWS Security features and troubleshooting methods, and developed AWS-centric applications based on an underlying AWS infrastructure.
This fast-paced guide will quickly enhance your skills to develop a highly scalable Cloud environment Key Features Efficiently build a highly scalable and reliable cloud environment for your applications with AWS Leverage the various AWS components and services to build a secure, reliable, and robust environment to host your applications on This quick-start guide will quickly enhance your skills to develop highly scalable services Book Description AWS is at the forefront of Cloud Computing today. Businesses are adopting AWS Cloud because of its reliability, versatility, and flexible design. The main focus of this book is teaching you how to build and manage highly reliable and scalable applications and services on AWS. It will provide you with all the necessary skills to design, deploy, and manage your applications and services on the AWS cloud platform. We’ll start by exploring Amazon S3, EC2, and so on to get you well-versed with core Amazon services. Moving on, we’ll teach you how to design and deploy highly scalable and optimized workloads. You’ll also discover easy-to-follow, hands-on steps, tips, and recommendations throughout the book and get to know essential security and troubleshooting concepts. By the end of the book, you’ll be able to create a highly secure, fault tolerant, and scalable environment for your applications to run on. What you will learn Find out about IAM to access AWS services securely Explore EC2 (virtual server) and scale up/down your application based on heavy traffic Learn about unlimited data storage service S3 and host a static website within minutes Get to grips with Relational Databases and NoSQL databases under the AWS ecosystem Understand the caching mechanism Get to know about notifications service and monitor AWS services Secure and troubleshoot your AWS architecture Who this book is for This book is for IT professionals and system administrators looking to design, deploy, and manage your applications and services on the AWS cloud platform. It’s also ideal for developers looking to build highly scalable cloud-based services. A basic understanding of AWS would be beneficial.
Work through exciting recipes to administer your AWS cloud Key Features Build secure environments using AWS components and services Explore core AWS features with real-world applications and best practices Design and build Lambda functions using real-world examples Book Description With this Learning Path, you’ll explore techniques to easily manage applications on the AWS cloud. You’ll begin with an introduction to serverless computing, its advantages, and the fundamentals of AWS. The following chapters will guide you on how to manage multiple accounts by setting up consolidated billing, enhancing your application delivery skills, with the latest AWS services such as CodeCommit, CodeDeploy, and CodePipeline to provide continuous delivery and deployment, while also securing and monitoring your environment's workflow. It’ll also add to your understanding of the services AWS Lambda provides to developers. To refine your skills further, it demonstrates how to design, write, test, monitor, and troubleshoot Lambda functions. By the end of this Learning Path, you’ll be able to create a highly secure, fault-tolerant, and scalable environment for your applications. This Learning Path includes content from the following Packt products: AWS Administration: The Definitive Guide, Second Edition by Yohan Wadia AWS Administration Cookbook by Rowan Udell, Lucas Chan Mastering AWS Lambda by Yohan Wadia, Udita Gupta What you will learn Explore the benefits of serverless computing and applications Deploy apps with AWS Elastic Beanstalk and Amazon Elastic File System Secure environments with AWS CloudTrail, AWSConfig, and AWS Shield Run big data analytics with Amazon EMR and Amazon Redshift Back up and safeguard data using AWS Data Pipeline Create monitoring and alerting dashboards using CloudWatch Effectively monitor and troubleshoot serverless applications with AWS Design serverless apps via AWS Lambda, DynamoDB, and API Gateway Who this book is for This Learning Path is specifically designed for IT system and network administrators, AWS architects, and DevOps engineers who want to effectively implement AWS in their organization and easily manage daily activities. Familiarity with Linux, web services, cloud computing platforms, virtualization, networking, and other administration-related tasks will assist in understanding the concepts in the book. Prior hands-on experience with AWS core services such as EC2, IAM, S3, and programming languages, such as Node.Js, Java, and C#, will also prove beneficial.
Over 90 hands-on recipes to design Internet scalable web and mobile applications with Amazon DynamoDB About This Book Construct top-notch mobile and web applications with the Internet scalable NoSQL database and host it on cloud Integrate your applications with other AWS services like AWS EMR, AWS S3, AWS Redshift, and AWS CloudSearch etc. in order to achieve a one-stop application stack Step-by-step implementation guide that provides real-world use with hands-on recipes Who This Book Is For This book is intended for those who have a basic understanding of AWS services and want to take their knowledge to the next level by getting their hands dirty with coding recipes in DynamoDB. What You Will Learn Design DynamoDB tables to achieve high read and write throughput Discover best practices like caching, exponential back-offs and auto-retries, storing large items in AWS S3, storing compressed data etc. Effectively use DynamoDB Local in order to make your development smooth and cost effective Implement cost effective best practices to reduce the burden of DynamoDB charges Create and maintain secondary indexes to support improved data access Integrate various other AWS services like AWS EMR, AWS CloudSearch, AWS Pipeline etc. with DynamoDB In Detail AWS DynamoDB is an excellent example of a production-ready NoSQL database. In recent years, DynamoDB has been able to attract many customers because of its features like high-availability, reliability and infinite scalability. DynamoDB can be easily integrated with massive data crunching tools like Hadoop /EMR, which is an essential part of this data-driven world and hence it is widely accepted. The cost and time-efficient design makes DynamoDB stand out amongst its peers. The design of DynamoDB is so neat and clean that it has inspired many NoSQL databases to simply follow it. This book will get your hands on some engineering best practices DynamoDB engineers use, which can be used in your day-to-day life to build robust and scalable applications. You will start by operating with DynamoDB tables and learn to manipulate items and manage indexes. You will also discover how to easily integrate applications with other AWS services like EMR, S3, CloudSearch, RedShift etc. A couple of chapters talk in detail about how to use DynamoDB as a backend database and hosting it on AWS ElasticBean. This book will also focus on security measures of DynamoDB as well by providing techniques on data encryption, masking etc. By the end of the book you'll be adroit in designing web and mobile applications using DynamoDB and host it on cloud. Style and approach An easy-to-follow guide, full of real-world examples, which takes you through the world of DynamoDB following a step-by-step, problem-solution based approach.
Get a fundamental understanding of how Google BigQuery works by analyzing and querying large datasets About This Book Get started with BigQuery API and write custom applications using it Learn how BigQuery API can be used for storing, managing, and query massive datasets with ease A practical guide with examples and use-cases to teach you everything you need to know about Google BigQuery Who This Book Is For If you are a developer, data analyst, or a data scientist looking to run complex queries over thousands of records in seconds, this book will help you. No prior experience of working with BigQuery is assumed. What You Will Learn Get a hands-on introduction to Google Cloud Platform and its services Understand the different data types supported by Google BigQuery Migrate your enterprise data to BigQuery and query it using the legacy and standard SQL techniques Use partition tables in your project and query external data sources and wild card tables Create tables and data sets dynamically using the BigQuery API Perform real-time inserting of records for analytics using Python and C# Visualize your BigQuery data by connecting it to third party tools such as Tableau and R Master the Google Cloud Pub/Sub for implementing real-time reporting and analytics of your Big Data In Detail Google BigQuery is a popular cloud data warehouse for large-scale data analytics. This book will serve as a comprehensive guide to mastering BigQuery, and how you can utilize it to quickly and efficiently get useful insights from your Big Data. You will begin with getting a quick overview of the Google Cloud Platform and the various services it supports. Then, you will be introduced to the Google BigQuery API and how it fits within in the framework of GCP. The book covers useful techniques to migrate your existing data from your enterprise to Google BigQuery, as well as readying and optimizing it for analysis. You will perform basic as well as advanced data querying using BigQuery, and connect the results to various third party tools for reporting and visualization purposes such as R and Tableau. If you're looking to implement real-time reporting of your streaming data running in your enterprise, this book will also help you. This book also provides tips, best practices and mistakes to avoid while working with Google BigQuery and services that interact with it. By the time you're done with it, you will have set a solid foundation in working with BigQuery to solve even the trickiest of data problems. Style and Approach This book follows a step-by-step approach to teach readers the concepts of Google BigQuery using SQL. To explain various data querying processes, large-scale datasets are used wherever required.