In this article we would like to give you a high level summary on Azure Synapse.
What it is, what are its strengths and weaknesses observed through our project implementations and what are the major benefits the stakeholders got the most value from and what main features the developers and architects were interested in.
What is Azure Synapse?
Azure Synapse Analytics is a unique platform for analytics combining big data, data warehousing and data integration in a single cloud native service for end-to-end analytics at scale.
At Joyful Craftsmen we worked with Azure Synapse Analytics together with Microsoft since its inception before it became publicly available for production.
Since then, we have done a lot of work with our clients on Azure Synapse Analytics and during our projects with Azure Synapse which we are delivering successfully for our clients, we experienced the following strengths and weaknesses.
- all-in-one cloud service service for analytics
- easy to set up, use and manage
- integration with Microsoft services
- steep learning curve for Microsoft data engineers
- technical limitations to cooperate with other technologies
Most Valuable Benefits of Azure Synapse
- Ready to use single cloud service saving integration costs of various services for big data, data warehousing and data integration compared to other platforms
- Auto machine learning insights into your data and saves costs on starting with machine learning
- Data governance ready to fulfill regulatory requirements for data lineage adding data discovery which is saving lots of effort when building applications and reporting on top of data
- Quick delivery of reporting and insights into data with Power BI
- Steep learning curve for people working with Microsoft SQL Server based data warehouses saving costs learning new technologies
- One of the best price/performance results in industry benchmarks of cloud data warehouses
Detailed Major Features of Azure Synapse
- Azure Synapse Studio – integrated development environment
- Azure Synapse Dedicated Pool – dedicated clusters for mission critical data warehouse workloads
- Azure Synapse Serverless Pool – pay per query ideal for ad-hoc data lake exploration and transformation
- Azure Synapse Spark Pool – data processing with Spark
- Azure Data Lake as source for Azure pools
- Power BI for reporting front-end
- Azure Machine Learning and Auto ML features with pre-build models and low-code no-code approach
- Purview for easy data governance
- Azure Data Share for data sharing
- Azure Synapse Link to Dataverse for easy data ingestion from Power Platform
- Azure Synapse Link to Cosmos DB for real time operations analytics
- Scale in with workload importance or workload isolation helps mainz to provide predictable costs
- Scale out with elastic cluster to increase performance during query intensive loads
- all data encrypted by default
- fine grained access control
- proactive protection
- comprehensive compliance
- Ingesting on-prem, cloud, SaaS and streaming data
- Azure Data Factory like pipelines
- Code free data wrangling using Power Query to prepare data
- Prepared solution templates to accelerate time to solution
- open Azure Data sets
- Industry specific data models
- SQL scripts
Whom we helped with Azure Synapse
I’m working with SQL Server and Microsoft Data platform over 10 years. I worked in this area from MS BI application solution development through MS BI infrastructure projects to pre-sales engineer. I like Microsoft BI very much and I follow the new trends in this area as well as the competition technologies. The most important for me is that I advance with experience and know how in this area.
Co-owner & CBDO