
Discover strategies for migrating to Power BI Report Server, utilizing ReportServer database metadata to determine which reports and data sources to migrate, and learn PowerShell techniques for efficient extraction and migration.

Discover lesser-known features and improvements in SQL Server 2019 beyond the main highlights, exploring hidden capabilities that can enhance database management and performance.

Explore Azure Hyperscale: a cloud-native, scalable database solution offering SQL Server features for innovation and future-proofing. Learn deployment patterns, best practices, and its underlying architecture.

Explore Azure Data Studio's features, benefits, and comparison to SQL Server Management Studio. Learn about its cross-platform capabilities, monitoring tools, and use cases.

Explore SQL Server 2019's Batch Execution Mode for Rowstore Indexes, its benefits, challenges, and optimal usage scenarios to significantly enhance workload performance.

Explore efficient SQL Server solution deployment using containers, covering basic and advanced methods, real-world scenarios, and cross-platform portability for streamlined database management.

Explore command-line tools for managing SQL Server on Linux, including installation, configuration, and monitoring. Learn to leverage bash for querying DMVs and gain insights for seasoned command-line users.

Learn to automate database operations and deployments for efficient management of hundreds of databases, meeting industry demands for faster, streamlined processes.

Discover best practices, tips, and monitoring techniques for optimizing Azure SQL Database performance in production environments, based on real-world Microsoft CSS support cases and customer engagements.

Comprehensive guide to building and deploying business apps using Microsoft Power Platform, covering PowerApps, Flow, SQL Server, Power BI, and Cortana with focus on security and enterprise governance.

Explore SQL Server execution plans to optimize query performance. Learn to capture, read, and analyze plans, identifying potential issues and understanding key operations for efficient database queries.

Learn to set up, use, and deploy CosmosDB for globally distributed, scalable database solutions. Explore JSON data loading, PowerBI visualization, and seamless cloud migration.

Explore SQL Server's native encryption methods, Azure Key Vault, and Always Encrypted to safeguard your data. Learn implementation techniques and potential issues for modern data security.

Explore new features for migrating legacy SSIS to Azure Data Factory, including Azure-SSIS Integration Runtime, Azure Files integration, and batch assessments using Data Migration Assistant.

Explore SQL Server's cardinality estimation process to optimize query performance. Learn how to influence physical operations, handle multiple predicates, and tackle complex query plans.

Explore Google Cloud SQL for SQL Server: architecture, provisioning, analytics, security, high availability, and replication. Learn best practices and tools for leveraging this managed database service.

Explore VertiPaq engine internals, database architecture, and optimization techniques for improved performance and compression in SQL Server Analysis Services Tabular, Power BI, and Power Pivot.

Learn to implement Database DevOps using SQL Server containers, Flyway, Kubernetes, and Azure DevOps. Explore strategies for efficient database migrations and build your first CI/CD pipeline for database deployment.

Learn to optimize Azure SQL Database serverless for intermittent workloads, automatically scaling resources and improving cost-efficiency while simplifying performance management.

Explore Azure Data Engineer role: certifications, skills, and duties. Learn about storage, security, DevOps, and automation. Gain insights for certification exams and career advancement in cloud data engineering.

Learn to deploy database code consistently and accurately using Azure DevOps pipeline. Explore techniques for setting up database objects, including security and reports, for successful and repeatable deployments across different environments.