Azure Blockchain Service serves as a secure and transparent transaction ledger, ensuring the integrity and transparency of transactions across a distributed network.

Azure Machine Learning supports the creation and deployment of models through automated machine learning (AutoML), allowing users to build models efficiently with minimal manual coding.

Azure Information Protection (AIP) allows users to label sensitive information, helping in the classification and subsequent application of appropriate protection policies.

Azure Synapse Analytics seamlessly integrates with Azure Synapse Studio, Azure Machine Learning, Azure Databricks, and Azure Logic Apps to enable advanced analytics and streamline data processing workflows.

Azure Storage Service Encryption (SSE) enhances data security by encrypting data at rest, ensuring that even if unauthorized access occurs, the data remains protected.

The Auto-Remediation feature in Azure Security Center automates the application of security controls, enhancing the security posture across different Azure services.

Azure Edge Computing often integrates Artificial Intelligence (AI) technology to enhance computational capabilities at the edge, allowing for intelligent processing of data.

In ADO.NET, the Savepoint feature is used for partial rollback within a transaction, allowing specific parts of the transaction to be undone while preserving the rest.

Disabling lazy loading can improve the performance of Entity Framework queries when dealing with large datasets. Lazy loading is the default behavior in Entity Framework, where related entities are loaded from the database only when they are accessed for the first time. This can lead to numerous database round-trips when dealing with large datasets, resulting in poor performance. By disabling lazy loading, all related entities are eagerly loaded along with the main entity, reducing the number of database round-trips and improving query performance. However, it's essential to consider the trade-offs, such as increased memory usage, when disabling lazy loading.

The group by clause in LINQ to DataSet is used to group data based on related columns. It allows you to organize your data into groups based on a specified column or columns, facilitating easier analysis and processing of grouped data.