ML and Better Data Protection

ML models can be used in the scope of analysis by Azure Synapse Analytics and SQL Server 2022. Real-time analysis of streaming data is also supported, for example, if the data has been integrated directly into a data warehouse. To this end, Azure Synapse Analytics integrates the Spark engine and can therefore collaborate with SQL Server 2022.

Microsoft has also integrated data protection functions into the system and made it possible to analyze individual columns and rows with different security settings and permissions. Dynamic data masking is possible, as is permanent encryption of all data. The system uses other Azure technologies to detect threats and can automatically protect the data being analyzed. Azure Synapse Analytics relies on Azure Active Directory for authentication.

In addition to data protection, data sharing naturally plays an important role. Azure Data Share [4] is one of the options available. The service works directly with Azure Synapse Analytics, enabling data sharing through the Azure user interface (e.g., in the scope of a subscription). In general, all software-as-a-service (SaaS) components that support the Open Data Initiative [5] can be connected.

Queries via SQL

The data in Azure Synapse Analytics can be queried by SQL. In this way, both relational and non-relational data (e.g., originating from local servers running SQL Server 2022) can be analyzed. According to Microsoft, petabytes of data can be processed in just seconds. In this context, Synapse Analytics supports Power BI and Azure Machine Learning. Power BI capabilities are integrated directly into Azure Synapse Analytics for this purpose, including the numerous data sources that can be connected by Power BI. The Power BI Common Data Service (CDS) and artificial intelligence (AI) capabilities are also available in Azure Synapse Analytics.

Azure Synapse Analytics supports other languages besides Transact SQL (T-SQL) for analysis or for connecting external systems, including Python, Scala, Spark, and, of course, .NET. The functions from Azure Data Factory are also available in Azure Synapse Analytics. Data sources can be connected to Mapping Data Flows, which is a graphical ETL tool available directly in the Synapse workspace.

Data Analytics and Blockchain Technologies

Azure Purview is another service related to SQL Server 2022. It supports the establishment of consistent governance functions for on-premises systems in the same way as in the cloud. The service captures the metadata on the on-premises SQL servers and classifies the data. Azure Purview helps organizations catalog and manage their data wherever the data resides. Access rights can be controlled specifically for local SQL servers.

SQL Server Ledger, on the other hand, is a data integrity technology. It can be used, for example, to store off-chain data from blockchains, such as for smart contracts or decentralized apps (dApps). However, SQL Ledger also ensures that certain data cannot be changed, ruling out manipulation. In this regard, SQL Server 2022 can demonstrate that data integrity has not been compromised whenever needed by a client.