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Cloud Analytics with Google Cloud Platform : an end-to-end guide to processing and analyzing big data using Google Cloud Platform.
This book will deep-dive into the concept of analytics on the cloud with the design and business considerations. You will build an end-to-end analytics engine to perform smart analytics using machine learning and deep learning concepts. From ingestion to processing your data, this book contains the...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing,
2018.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Thodge, Sanket. | |
| 245 | 1 | 0 | |a Cloud Analytics with Google Cloud Platform : |b an end-to-end guide to processing and analyzing big data using Google Cloud Platform. |
| 260 | |a Birmingham : |b Packt Publishing, |c 2018. | ||
| 300 | |a 1 online resource (273 pages) | ||
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| 505 | 0 | |a Cover; Title Page; Copyright and Credits; Packt Upsell; Foreword; Contributors; Table of Contents; Preface; Chapter 1: Introducing Cloud Analytics; What is cloud computing?; Major benefits of cloud computing; Cloud computing deployment models; Private cloud; Public cloud; Hybrid cloud; Differences between the private cloud, hybrid cloud, and public cloud models; Types of cloud computing services; Infrastructure as a Service; PaaS; SaaS; Differences between SaaS, PaaS, and IaaS; How PaaS, IaaS, and SaaS are separated at service level; Emerging cloud technologies and services. | |
| 505 | 8 | |a Different ways to secure the cloudRisks and challenges with the cloud; What is cloud analytics?; 10 major cloud vendors in the world; Google Cloud Platform introduction-video; Summary; Chapter 2: Design and Business Considerations; A bit more about cloud computing and migration; Parameters before adopting cloud strategy; Developing and changing business needs; Security of data; Organizational requests on the in-house IT team; Cloud deployment models-public cloud, private cloud, and hybrid cloud; Legally binding responsibilities; Prerequisites for an application to be moved to the cloud. | |
| 505 | 8 | |a PerformancePortability; Simplifying cloud migration with virtualization; Infrastructure contemplation for cloud; Available deployment models while moving to cloud; IaaS; Advantages of IaaS; Disadvantages of IaaS; PaaS; Advantages of PaaS; Disadvantages of PaaS; SaaS; Cloud migration checklist; Architecture of a cloud computing ecosystem; Infrastructure for cloud computing; Constrictions on cloud infrastructure; Applications of cloud computing; Preparing a plan for moving to cloud computing; Methodology stage; Cloud computing proposal worth; Cloud computing methodology planning; Planning stage. | |
| 505 | 8 | |a Distribution stageMaking arrangements for a multi-provider methodology; Making a multi-provider design tactic; Technologies utilized by cloud computing; Grid computing; Service-oriented architecture; Virtualization; Utility computing; Summary; Chapter 3: GCP 10,000 Feet Above -- A High-Level Understanding of GCP; Different services offered by typical cloud vendors; Understanding cloud categories; Compute; Compute Engine; App engine; Kubernetes engine; Cloud function; Storage and databases; Cloud storage; Cloud SQL; Cloud Bigtable; Cloud Spanner; Cloud Datastore; Persistent Disk; Networking. | |
| 505 | 8 | |a Virtual Private CloudCloud load balancing; Cloud CDN; Cloud interconnect; Cloud DNS; Network Service Tiers ALPHA; Big Data; BigQuery; Cloud Dataflow; Cloud Dataproc; Cloud Datalab; Cloud Dataprep BETA; Cloud Pub/Sub; Genomics; Google Data Studio BETA; Data transfer; Google Transfer appliance; Cloud Storage Transfer Service; Google BigQuery Data Transfer Service; Cloud AI; Cloud AutoML alpha; Cloud TPU beta; Cloud machine learning engine; Cloud job discovery private beta; Dialogflow enterprise edition beta; Cloud natural language; Cloud speech API, translation API, and vision API. | |
| 500 | |a Cloud video intelligence. | ||
| 520 | |a This book will deep-dive into the concept of analytics on the cloud with the design and business considerations. You will build an end-to-end analytics engine to perform smart analytics using machine learning and deep learning concepts. From ingestion to processing your data, this book contains the best practices using Google Cloud Platform. | ||
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| 650 | 0 | |a Web applications. | |
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| 776 | 0 | 8 | |i Print version: |a Thodge, Sanket. |t Cloud Analytics with Google Cloud Platform : An end-to-end guide to processing and analyzing big data using Google Cloud Platform. |d Birmingham : Packt Publishing, ©2018 |
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