Gartner Research

Architecting Data and Analytics Pipelines in Azure

Published: 17 June 2019

ID: G00377900

Analyst(s): Sanjeev Mohan

Summary

Microsoft Azure continues to innovate, evolve and expand as cloud deployments accelerate. Data and analytics technical professionals must assess the data storage, transformation and management capabilities of Azure to build highly performant end-to-end analytics pipelines and architectures.

Table Of Contents

Analysis

  • Ingestion
    • Azure Data Factory (ADF)
    • Azure Event Hubs
    • Third-Party Ingestion Options
    • Azure Stream Analytics
  • Data Integration and Transformation
    • Azure Data Factory (ADF)
    • Azure Databricks
    • Azure HDInsight
    • Third-Party Integration and Transformation Options
  • Data Persistence
    • Azure Data Lake Store (ADLS) Gen2
    • Common Data Model (CDM)
    • Azure SQL Database (SQL DB)
    • Azure Database for MySQL, PostgreSQL and MariaDB
    • Why Clients Should Consider Azure Database
    • Azure SQL Data Warehouse (SQL Data Warehouse)
    • Azure Cosmos DB
    • Azure Cache for Redis
  • Analytics
    • Power BI
    • Azure Analysis Services (AAS)
    • Azure Data Explorer (ADX)
  • Advanced Analytics
  • Data Governance
  • Strengths
  • Weaknesses

Guidance

The Details

  • Modern Data Warehouse
    • Current State
    • Future State
  • Real-Time Analytics
  • Azure IoT Architecture

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