Microsoft Streamlines Cloud Analytics with Azure Synapse Analytics

by Ross McNeely

Practice Manager, Enterprise Data Management

A year ago, I gave a 3-hour presentation titled ‘Analytics in the Cloud’ to industry professionals.  The presentation covered enterprise analytics, and used the following tools Azure Data Factory, Azure Data Lake Storage, Azure Databricks, and Azure Machine Learning.  Each tool has a separate portal to manage.  It was an advanced level session.  Today, I can give the same presentation, and stay within the Azure Synapse Studio.   

Azure Synapse provides enterprise with scalable data performance, security, query language flexibility, and machine learning in a unified interface.  You have the option to provision a dedicated instance, or run on demand based on your workload.  The analytics runtime includes T-SQL for batch, streaming, interactive processing.  A Spark runtime is there for big data processing with Python, Scala, R, and .Net.  In Azure Synapse you develop data integrations uses notebooks, SQL scripts, or data flows to define the business logic for pipelines.  Finally, you can create Power BI reports in the Azure Synapse workspace and publish. 

Today's Modern Data Warehouse Approach
Last Year's Modern Data Warehouse Approach

Azure Synapse Scenarios
• Large volumes of data
• Producing a Single-Version-of-Truth from siloed data
• Ad-hoc analysis on large data sets
• Query performance for analytical reports
• Bring your query language (SQL, Python, Scala, R, Java, .NET)
• Batch loads