Microsoft Synapse Analytics provides a unified analytics service that spans data warehousing, data lakes, and business intelligence. 

With Synapse, you can rapidly query vast datasets and build machine learning models to power data-driven decisions.

The Need for Unified Analytics

Traditionally, analytics required stitching together separate systems for data warehousing, data lakes, and BI. This led to silos of data that were hard to access and analyze together.

Microsoft Synapse eliminates these silos with a single service for limitless analytics. Synapse enables businesses to:

  • Query data warehouses and lakes together via SQL and Spark
  • Create unified data models and pipelines
  • Apply machine learning anywhere across the data estate
  • Share insights using built-in BI capabilities

With Synapse, you break down data barriers to gain deeper connections and insights.

Key Capabilities and Benefits

Synapse Analytics includes several key capabilities for unified data analytics:

SQL and Spark Pools

Synapse allows running SQL and Spark workloads on-demand or provisioned, for both structured and unstructured data. This means one service for all your analytics needs.

Integrated Machine Learning

Build AI models with Azure Machine Learning integrated into Synapse. Score, train, and deploy models across SQL and Spark to infuse your analytics with predictive power.

Enterprise Security

Manage and secure data access through fine-grained, role-based access controls. Integrate with Active Directory and Azure for identity and access management.

Native Business Intelligence

Embed Power BI reports and dashboards natively in Synapse for easy sharing of insights. Synapse handles BI workload provisioning automatically.

Code-Free ETL Pipelines

Synapse’s data integration service enables no-code ETL pipelines to ingest, transform, and load data into warehouses, lakes, and BI tools.

microsoft synapse analytics

Unified Analytics in Action

Let’s look at a hypothetical retail scenario to see unified analytics in action:

  • SQL pools query POS and ERP system data loaded into Synapse data warehouses.
  • Spark pools analyze clickstream data from apps and websites stored in Cosmos DB or ADLS data lakes.
  • Machine learning models are built and deployed across SQL and Spark for predictions.
  • BI dashboards visualize sales, inventory, and customer analytics.
  • Secure role-based access ensures teams see only relevant data.

By supporting SQL, Spark, ML, and BI in one service, Synapse can deliver deeper, faster insights across your data estate.

Get Started with Microsoft Synapse Analytics

Ready to unlock unified analytics for your business? Here are suggested steps to get started with Microsoft Synapse:

  • Discover data sources across your warehouses, lakes, apps, and BI systems.
  • Provision SQL and Spark pools for analytics workloads in Synapse.
  • Ingest data into Synapse using ETL pipelines.
  • Query data together using SQL and Spark notebooks.
  • Build models using Azure ML integration in Synapse.
  • Create BI dashboards and reports in Power BI linked to Synapse.
  • Manage access controls to secure data.

With the power of Synapse’s unified analytics, you can tap into all your data to drive deeper insights for your organization.

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