Gartner Research

Building Data and Analytics Architecture in Google Cloud Platform

Published: 13 April 2020

ID: G00451418

Analyst(s): Sanjeev Mohan

Summary

Google Cloud Platform is a comprehensive and enterprise-ready solution to deliver complex analytical pipelines and workloads. Data and analytics technical professionals should assess GCP’s expanding capabilities to build highly performant, scalable, secure and reliable end-to-end architectures.

Table Of Contents

Analysis

  • Ingestion
    • Cloud Pub/Sub
  • Data Integration and Transformation
    • Cloud Dataflow
  • Data Persistence
    • Google Cloud Storage (GCS)
    • Cloud SQL
    • Cloud Spanner
    • Cloud Firestore (Cloud Datastore)
    • Cloud Bigtable
    • BigQuery
    • Nonnative Databases
    • Data Migration
  • Analytics
    • BI With BigQuery
    • Looker
    • Data Studio
  • Machine Learning and Artificial Intelligence
  • Data Security, Privacy and Governance
    • Data Catalog
    • Cloud DLP
    • Data Security (Cloud KMS, Cloud EKM and Cloud IAM)
  • Data Orchestration
    • Cloud Composer
    • Stackdriver
    • Anthos
    • DevOps/DataOps
  • Strengths
  • Weaknesses

Guidance

The Details

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