Author: Dan Sullivan
Publisher: John Wiley & Sons
ISBN: 1119618436
Category : Computers
Languages : en
Pages : 357

View

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: Matt Fuller
Publisher: O'Reilly Media
ISBN: 1492044245
Category : Computers
Languages : en
Pages : 310

View

Book Description
Perform fast interactive analytics against different data sources using the Presto high-performance, distributed SQL query engine. With this practical guide, you’ll learn how to conduct analytics on data where it lives, whether it’s Hive, Cassandra, a relational database, or a proprietary data store. Analysts, software engineers, and production engineers will learn how to manage, use, and even develop with Presto. Initially developed by Facebook, open source Presto is now used by Netflix, Airbnb, LinkedIn, Twitter, Uber, and many other companies. Matt Fuller, Manfred Moser, and Martin Traverso show you how a single Presto query can combine data from multiple sources to allow for analytics across your entire organization. Get started: Explore Presto’s use cases and learn about tools that will help you connect to Presto and query data Go deeper: Learn Presto’s internal workings, including how to connect to and query data sources with support for SQL statements, operators, functions, and more Put Presto in production: Secure Presto, monitor workloads, tune queries, and connect more applications; learn how other organizations apply Presto

Author: Jeff Carpenter
Publisher: O'Reilly Media
ISBN: 1098115139
Category : Computers
Languages : en
Pages : 429

View

Book Description
Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition—updated for Cassandra 4.0—provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s nonrelational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility. Understand Cassandra’s distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell Create a working data model and compare it with an equivalent relational model Develop sample applications using client drivers for languages including Java, Python, and Node.js Explore cluster topology and learn how nodes exchange data

Author: Rajdeep Chakraborty
Publisher: John Wiley & Sons
ISBN: 1119764092
Category : Computers
Languages : en
Pages : 484

View

Book Description
MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITY This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions The aim of Machine Learning Techniques and Analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security. Cloud security with ML has long-standing challenges that require methodological and theoretical handling. The conventional cryptography approach is less applied in resource-constrained devices. To solve these issues, the machine learning approach may be effectively used in providing security to the vast growing cloud environment. Machine learning algorithms can also be used to meet various cloud security issues, such as effective intrusion detection systems, zero-knowledge authentication systems, measures for passive attacks, protocols design, privacy system designs, applications, and many more. The book also contains case studies/projects outlining how to implement various security features using machine learning algorithms and analytics on existing cloud-based products in public, private and hybrid cloud respectively. Audience Research scholars and industry engineers in computer sciences, electrical and electronics engineering, machine learning, computer security, information technology, and cryptography.

Author: Naveen Chilamkurti
Publisher: CRC Press
ISBN: 1000359557
Category : Computers
Languages : en
Pages : 400

View

Book Description
Blockchain, Internet of Things, and Artificial Intelligence provides an integrated overview and technical description of the fundamental concepts of blockchain, IoT, and AI technologies. State-of-the-art techniques are explored in depth to discuss the challenges in each domain. The convergence of these revolutionized technologies has leveraged several areas that receive attention from academicians and industry professionals, which in turn promotes the book's accessibility more extensively. Discussions about an integrated perspective on the influence of blockchain, IoT, and AI for smart cities, healthcare, and other business sectors illuminate the benefits and opportunities in the ecosystems worldwide. The contributors have focused on real-world examples and applications and highlighted the significance of the strengths of blockchain to transform the readers’ thinking toward finding potential solutions. The faster maturity and stability of blockchain is the key differentiator in artificial intelligence and the Internet of Things. This book discusses their potent combination in realizing intelligent systems, services, and environments. The contributors present their technical evaluations and comparisons with existing technologies. Theoretical explanations and experimental case studies related to real-time scenarios are also discussed. FEATURES Discusses the potential of blockchain to significantly increase data while boosting accuracy and integrity in IoT-generated data and AI-processed information Elucidates definitions, concepts, theories, and assumptions involved in smart contracts and distributed ledgers related to IoT systems and AI approaches Offers real-world uses of blockchain technologies in different IoT systems and further studies its influence in supply chains and logistics, the automotive industry, smart homes, the pharmaceutical industry, agriculture, and other areas Presents readers with ways of employing blockchain in IoT and AI, helping them to understand what they can and cannot do with blockchain Provides readers with an awareness of how industry can avoid some of the pitfalls of traditional data-sharing strategies This book is suitable for graduates, academics, researchers, IT professionals, and industry experts.

Author: AS
Publisher: AS [Author]
ISBN:
Category : Business & Economics
Languages : en
Pages : 77

View

Book Description
How to Start a Business About the Book: Unlock the essential steps to launching and managing a successful business with How to Start a Business books. Part of the acclaimed How to Start a Business series, this volume provides tailored insights and expert advice specific to the industry, helping you navigate the unique challenges and seize the opportunities within this field. What You'll Learn Industry Insights: Understand the market, including key trends, consumer demands, and competitive dynamics. Learn how to conduct market research, analyze data, and identify emerging opportunities for growth that can set your business apart from the competition. Startup Essentials: Develop a comprehensive business plan that outlines your vision, mission, and strategic goals. Learn how to secure the necessary financing through loans, investors, or crowdfunding, and discover best practices for effectively setting up your operation, including choosing the right location, procuring equipment, and hiring a skilled team. Operational Strategies: Master the day-to-day management of your business by implementing efficient processes and systems. Learn techniques for inventory management, staff training, and customer service excellence. Discover effective marketing strategies to attract and retain customers, including digital marketing, social media engagement, and local advertising. Gain insights into financial management, including budgeting, cost control, and pricing strategies to optimize profitability and ensure long-term sustainability. Legal and Compliance: Navigate regulatory requirements and ensure compliance with industry laws through the ideas presented. Why Choose How to Start a Business books? Whether you're wondering how to start a business in the industry or looking to enhance your current operations, How to Start a Business books is your ultimate resource. This book equips you with the knowledge and tools to overcome challenges and achieve long-term success, making it an invaluable part of the How to Start a Business collection. Who Should Read This Book? Aspiring Entrepreneurs: Individuals looking to start their own business. This book offers step-by-step guidance from idea conception to the grand opening, providing the confidence and know-how to get started. Current Business Owners: Entrepreneurs seeking to refine their strategies and expand their presence in the sector. Gain new insights and innovative approaches to enhance your current operations and drive growth. Industry Professionals: Professionals wanting to deepen their understanding of trends and best practices in the business field. Stay ahead in your career by mastering the latest industry developments and operational techniques. Side Income Seekers: Individuals looking for the knowledge to make extra income through a business venture. Learn how to efficiently manage a part-time business that complements your primary source of income and leverages your skills and interests. Start Your Journey Today! Empower yourself with the insights and strategies needed to build and sustain a thriving business. Whether driven by passion or opportunity, How to Start a Business offers the roadmap to turning your entrepreneurial dreams into reality. Download your copy now and take the first step towards becoming a successful entrepreneur! Discover more titles in the How to Start a Business series: Explore our other volumes, each focusing on different fields, to gain comprehensive knowledge and succeed in your chosen industry.

Author: Adi Wijaya
Publisher: Packt Publishing Ltd
ISBN: 1835085369
Category : Computers
Languages : en
Pages : 476

View

Book Description
Become a successful data engineer by building and deploying your own data pipelines on Google Cloud, including making key architectural decisions Key Features Get up to speed with data governance on Google Cloud Learn how to use various Google Cloud products like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream Boost your confidence by getting Google Cloud data engineering certification guidance from real exam experiences Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe second edition of Data Engineering with Google Cloud builds upon the success of the first edition by offering enhanced clarity and depth to data professionals navigating the intricate landscape of data engineering. Beyond its foundational lessons, this new edition delves into the essential realm of data governance within Google Cloud, providing you with invaluable insights into managing and optimizing data resources effectively. Written by a Data Strategic Cloud Engineer at Google, this book helps you stay ahead of the curve by guiding you through the latest technological advancements in the Google Cloud ecosystem. You’ll cover essential aspects, from exploring Cloud Composer 2 to the evolution of Airflow 2.5. Additionally, you’ll explore how to work with cutting-edge tools like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream to perform data governance on datasets. By the end of this book, you'll be equipped to navigate the ever-evolving world of data engineering on Google Cloud, from foundational principles to cutting-edge practices.What you will learn Load data into BigQuery and materialize its output Focus on data pipeline orchestration using Cloud Composer Formulate Airflow jobs to orchestrate and automate a data warehouse Establish a Hadoop data lake, generate ephemeral clusters, and execute jobs on the Dataproc cluster Harness Pub/Sub for messaging and ingestion for event-driven systems Apply Dataflow to conduct ETL on streaming data Implement data governance services on Google Cloud Who this book is for Data analysts, IT practitioners, software engineers, or any data enthusiasts looking to have a successful data engineering career will find this book invaluable. Additionally, experienced data professionals who want to start using Google Cloud to build data platforms will get clear insights on how to navigate the path. Whether you're a beginner who wants to explore the fundamentals or a seasoned professional seeking to learn the latest data engineering concepts, this book is for you.

Author: Joyce Kay Avila
Publisher: "O'Reilly Media, Inc."
ISBN: 1098103777
Category : Computers
Languages : en
Pages : 489

View

Book Description
Snowflake's ability to eliminate data silos and run workloads from a single platform creates opportunities to democratize data analytics, allowing users at all levels within an organization to make data-driven decisions. Whether you're an IT professional working in data warehousing or data science, a business analyst or technical manager, or an aspiring data professional wanting to get more hands-on experience with the Snowflake platform, this book is for you. You'll learn how Snowflake users can build modern integrated data applications and develop new revenue streams based on data. Using hands-on SQL examples, you'll also discover how the Snowflake Data Cloud helps you accelerate data science by avoiding replatforming or migrating data unnecessarily. You'll be able to: Efficiently capture, store, and process large amounts of data at an amazing speed Ingest and transform real-time data feeds in both structured and semistructured formats and deliver meaningful data insights within minutes Use Snowflake Time Travel and zero-copy cloning to produce a sensible data recovery strategy that balances system resilience with ongoing storage costs Securely share data and reduce or eliminate data integration costs by accessing ready-to-query datasets available in the Snowflake Marketplace

Author: Enamul Haque
Publisher: Enel Publication
ISBN:
Category : Computers
Languages : en
Pages : 295

View

Book Description
CLOUD COMPUTING ADOPTION TO VALUE CREATING A more straightforward guide for a more competent shift Your Complete Guide to Cloud Computing and Migrating to the Cloud. This book covers the technical details of how public and private cloud technology works and the strategy, technical design, and in-depth implementation details required to migrate existing applications to the cloud. After reading this book, you will have a much better understanding of cloud technology and the steps needed to quickly reap its benefits while at the same time lowering your IT implementation risk. Written by a proven expert in cloud computing, business management, network engineering, and IT security. This is a must-read for IT management, CIOs, senior IT engineers, and program managers in the government, DoD, and commercial sectors. Table of Contents Fundamental Cloud Computing Understanding Cloud Computing Fundamental Concepts and Models Cloud-Enabling Technology Fundamental Cloud Security Cloud Computing Mechanisms Cloud Infrastructure Mechanism Specialised Cloud Mechanisms Cloud Management Mechanisms Cloud Security Mechanisms Cloud Computing Architecture Fundamental Cloud Architectures Advanced Cloud Architectures Specialise Cloud Architectures Working with Clouds Cloud Delivery Model Considerations Cost Metrics and Pricing Models Service Quality Metrics and SLAs

Author: Josh Patterson
Publisher: "O'Reilly Media, Inc."
ISBN: 1492053228
Category : Computers
Languages : en
Pages : 331

View

Book Description
Building models is a small part of the story when it comes to deploying machine learning applications. The entire process involves developing, orchestrating, deploying, and running scalable and portable machine learning workloads--a process Kubeflow makes much easier. This practical book shows data scientists, data engineers, and platform architects how to plan and execute a Kubeflow project to make their Kubernetes workflows portable and scalable. Authors Josh Patterson, Michael Katzenellenbogen, and Austin Harris demonstrate how this open source platform orchestrates workflows by managing machine learning pipelines. You'll learn how to plan and execute a Kubeflow platform that can support workflows from on-premises to cloud providers including Google, Amazon, and Microsoft. Dive into Kubeflow architecture and learn best practices for using the platform Understand the process of planning your Kubeflow deployment Install Kubeflow on an existing on-premises Kubernetes cluster Deploy Kubeflow on Google Cloud Platform step-by-step from the command line Use the managed Amazon Elastic Kubernetes Service (EKS) to deploy Kubeflow on AWS Deploy and manage Kubeflow across a network of Azure cloud data centers around the world Use KFServing to develop and deploy machine learning models