Simplifying data landscape with Synapse

B 20 Reputation points
2024-09-13T13:46:14.5966667+00:00

How can I use Synapse to simplify my data landscape for maintenance and cost, assuming the lake is always a constant? I currently have two environments:

  1. Lake - Databricks(ETL) - Power BI
  2. Lake - ADF - AzureSQL - Analysis Services - Power BI

I'm not interested in Data Fabric right now and would appreciate some opinions and motivations to help me simplify my landscape.

Azure Analysis Services
Azure Analysis Services
An Azure service that provides an enterprise-grade analytics engine.
452 questions
Azure Synapse Analytics
Azure Synapse Analytics
An Azure analytics service that brings together data integration, enterprise data warehousing, and big data analytics. Previously known as Azure SQL Data Warehouse.
4,916 questions
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  1. Bhargava-MSFT 31,016 Reputation points Microsoft Employee
    2024-09-13T15:45:54.0533333+00:00

    Hello Bhavesh Bhana,

    Welcome to the Microsoft Q&A forum.

    To simplify your data landscape for maintenance and cost using Azure Synapse Analytics, you can consider consolidating your environments and leveraging the integrated capabilities of Synapse.

    Please see the below suggestions.

    • Consolidate ETL Processes: Instead of using separate tools like Databricks and Azure Data Factory for ETL, you can use Synapse Pipelines. Synapse Pipelines offer a fully managed, serverless data integration service that allows you to visually integrate data sources with more than 90 built-in, maintenance-free connectors at no added cost. This can help reduce the complexity and maintenance overhead of managing multiple ETL tools.
    • Unified Analytics Platform: Azure Synapse Analytics provides a unified platform for data warehousing and big data analytics. By moving your data processing and analytics workloads to Synapse, you can eliminate the need for separate Azure SQL and Analysis Services instances. Synapse offers capabilities like serverless SQL pools, dedicated SQL pools, and Apache Spark pools, which can handle various data processing and analytics tasks
    • Cost Management: Synapse provides various cost management features, such as the ability to set budgets, monitor costs, and review forecasted costs. You can use these features to identify areas where you can optimize costs and make informed decisions about resource allocation.
    • DirectQuery Power BI with Synapse: Instead of loading data into Power BI from Azure SQL or Analysis Services, you can use DirectQuery to query data directly from Synapse SQL pools or your data lake. Synapse integrates natively with Power BI, allowing reports to be dynamically generated from the lake or Synapse without data duplication.
    • Plan and Manage Costs: Use the Azure pricing calculator to estimate costs before adding any resources for Synapse. Review estimated costs in the Azure portal and use Cost Management features to set budgets and monitor costs. This can help you understand the full billing model for Synapse and identify areas where you can act to reduce costs
    • Pre-purchase Plans: Consider pre-purchasing Azure Synapse Analytics Commit Units (SCUs) to get up savings over pay-as-you-go prices. This can help you manage costs more effectively and take advantage of cost savings

    By consolidating your ETL processes, leveraging the unified analytics platform of Synapse, and using cost management features, you can simplify your data landscape and reduce maintenance and costs. If you have any specific questions, please let me know.

    I hope this helps.

    Reference documents:

    https://learn.microsoft.com/en-us/azure/synapse-analytics/plan-manage-costs

    https://learn.microsoft.com/en-us/azure/synapse-analytics/


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