Azure Synapse enables blazing-fast real-time scoring and inferencing using scale-out Apache Spark pools, optimized data stores like Azure SQL and Azure Storage, and seamless integration with Azure Synapse machine learning.
As a digital marketer in today’s data-driven world, leveraging real-time machine learning to extract insights and drive decision-making is crucial. With the meteoric rise of big data, performing real-time analytics at scale can be challenging. This is where Azure Synapse comes into play.
Azure Synapse is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless or provisioned resources at scale.
Let’s dive deeper into how Azure Synapse enables real-time scoring and inferencing using machine learning models at lightning speed.
Harness Serverless Apache Spark Pools
Azure Synapse allows you to create serverless Apache Spark pools that can scale on-demand to thousands of cores. This enables parallel execution of real-time scoring using Spark SQL and Spark Streaming against petabytes of data.
For example, you can connect a Spark pool directly to Azure Cosmos DB change feed to score new data as it arrives. Or tap into Kafka or Event Hubs streams for ultra-low latency scoring. The scale-out architecture ensures fast performance.
Operationalize Models using Optimized Data Stores
Azure Synapse provides seamless integration with Azure SQL and Azure Storage. This gives you a unified SQL interface to access data across these stores using serverless pools.
You can leverage Azure Machine Learning to bring trained models into Synapse SQL or Parquet tables. Then operationalize real-time scoring on new data via SQL queries or Spark jobs, with millisecond latency.
For instance, embed a demand forecasting model in Azure SQL. As new sales data arrives, run predictive queries using the model for real-time insights.
Seamlessly Manage ML Lifecycle End-to-End
Azure Synapse delivers first-class integration with Azure Machine Learning using Apache Spark. This enables direct model management capabilities like version tracking, deployment, monitoring, and retraining.
For example, you can train a churn prediction model in Azure ML, register it with Synapse via Spark, and then score user data in near real-time as it lands in Azure Storage. Get notified when the model needs retraining.
Real-World Success Stories
Here are some real-world examples of how brands have leveraged Azure Synapse’s real-time ML to drive impact:
- A Fortune 500 retail brand performs real-time scoring of customer micro-segments to deliver personalized recommendations. This increased sales by 14%.
- A healthcare company scales real-time clinical surveillance to millions of patients, enabling early disease intervention and improving outcomes.
- A global bank taps real-time ML on trading data to optimize investment strategies and risk management.
- A ride-sharing company scores driver and rider preferences in real-time to match supply and demand, reducing wait times.
The use cases are endless. Whatever your data scenario, Azure Synapse allows you to unlock real-time machine learning at unbelievable speeds.
Get Started Today
To summarize, Azure Synapse enables real-time scoring and inferencing using:
- Serverless Apache Spark pools
- Optimized data stores like Azure SQL and Azure Storage
- Tight integration with Azure Machine Learning
Ready to unlock limitless analytics and drive real-time intelligence? Get started with Azure Synapse today to transform your business.
