Cloud Analytics with Google Cloud Platform : an end-to-end guide to processing and analyzing big data using Google Cloud Platform.

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...

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Bibliographic Details
Main Author: Thodge, Sanket
Format: eBook
Language:English
Published: Birmingham : Packt Publishing, 2018.
Subjects:
Cloud computing.
Application software > Development.
Web applications.
COMPUTERS > Computer Literacy.
COMPUTERS > Computer Science.
COMPUTERS > Data Processing.
COMPUTERS > Hardware > General.
COMPUTERS > Information Technology.
COMPUTERS > Machine Theory.
COMPUTERS > Reference.
Application software > Development
Cloud computing
Web applications
Online Access:Click for online access
Table of Contents:
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.

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