3 steps to better models with SAS and Azure Synapse

All analytics projects have data as their foundation and this data is usually spread across a variety of databases, storage systems and locations. This diverse and complex landscape causes data scientists to spend an inordinate amount of time searching for the right data and preparing this information for analytics. It’s a frustrating, cumbersome and time consuming process. Fortunately, the new partnership between Microsoft and SAS provides a superior, unified analytical platform that allows data scientists to accelerate the data and analytics life cycle, driving projects swiftly to insights and decisions.

How it works

The platform combines the power of Azure Synapse and SAS® Viya® to offer a complete data and analytics solution. Azure Synapse is a unified platform for analytics, blending big data, data warehousing and data integration into a single cloud native service. It eliminates the silos between databases and data lakes and empowers customers to analyze any data at any scale.

The integrated web studio development environment enables developers to ingest, prepare, manage and serve data for scenarios ranging from descriptive reports to predictive machine learning. SAS Viya is a cloud native AI, analytic and data management platform that runs on a modern, scalable architecture. It’s designed to deliver better decisions, maximum value and trusted outcomes, regardless of the size or type of data, algorithm used, or how the analtyics are deployed.

SAS’ integration with Azure Synapse starts with connectivity and extends to native in-engine operationalization of models within the Synapse SQ engine. SAS Viya addresses the entire scope of analytics requirements, including machine learning, text analytics, computer vision, forecasting, econometrics and optimization.

Running natively on Microsoft Azure, SAS Viya scales to fit the scope of all analytics challenges, from experimental to mission critical. When combined with Azure Synapse, it’s easy to rapidly operationalize insights across the entire organization, enabling everyone to be more productive with data. SAS Viya and Azure Synapse empower everyone – data scientists, business analysts, developers and executives alike – to collaborate and realize innovative results faster.

Azure Synapse + SAS = unparalleled capabilities

The alignment of SAS Viya and Azure Synapse provides the data scientist community with a comprehensive analytical cloud-native environment to create, facilitate and manage the entire analytics life cycle.

Step 1:
First, data must be identified, accessed and consolidated for use. Azure Synapse has robust data integration capabilities including over 90 connectors to relational and non-relational databases as well as SaaS applications, that makes it easy to load data. This is where the magic of the partnership begins.

Step 2:
Once a data pipeline has been completed in Azure Synapse, SAS Viya can seamlessly access the data set inside of the Azure Synapse environment.

Step 3:
With SAS Viya, data scientists can build and generate automatic model pipelines. They can also easily weave open source R and Python models into the modeling pipelines and consider them in the modeling comparison exercise to identify the champion model. SAS provides natural language explanations of the model assesments, including model intepretability, so it’s easy for data scientists and business analysts to understand why one model was chosen over another, which provides transparency and trust in the outcome.

Managing and deploying models

Perhaps the most important part of any analytics effort is getting models into production so that they can be used to drive decisions. And once they’re in production, it’s critical to understand the model health and performance. SAS Model Manager on Viya is the perfect solution for registering, deploying and monitoring the well-being of these models. It provides for back testing and model tracking over time to ensure that when a model begins to decay, it’s refreshed, retrained or replaced to maintain optimal performance. Open source models get the same treatment, providing governance of all models.

When the best model has been identified it can be quickly published into production via model scoring APIs. This is key because the analytical scoring can be executed in-engine with Microsoft Azure Synapse, providing a highly scalable solution for calculating millions of predictions without the overhead of external API calls. Users with basic SQL skills are now empowered with analytical predictions. And because it’s just SQL, downstream systems or applications can also easily integrate to consume these predictions.

The bottom line

The combination of SAS and Microsoft in Azure Synapse provide data scientists with more options for methods, governance and scalability. The alignment brings a superior unified analytical platform not seen anywhere else in the market.

To learn more, watch the SAS and Azure demo below or visit our SAS and Microsoft partner site.