
Explore log-based Change Data Capture for SQL Server replication, covering file system-level CDC, DDL propagation, and type/version support for high-volume environments.

Explore the critical importance of selecting appropriate data types for optimal data quality, storage, performance, and query accuracy in database management.

Explore strategies to protect Azure data from regional outages, covering SQL Databases, VMs, and Managed Instances. Learn to meet recovery objectives and safeguard your cloud-based applications.

Explore modern data modeling trends for transactional applications, addressing challenges in NoSQL, microservices, and cloud environments. Learn to adapt traditional principles to meet current business demands and facilitate rapid changes.

Explore Azure Data Studio's features for managing data platforms, including dashboards, snippets, profiling, charting, and more. Learn when to use it over SQL Server Management Studio.

Explore JSON in databases: learn its origins, investigate, manipulate, and validate JSON data using Microsoft SQL Server tools and example code.

Comparative analysis of SSIS and Azure Data Factory, exploring strengths, weaknesses, and real-world applications for data movement and transformation in SQL Server environments.

Learn to automate SQL Server database deployments using Azure Pipelines and Visual Studio Database Projects. Covers creating projects, manual deployments, and setting up automated pipelines with secure credential management.

Explore multi-cloud strategies, benefits, and challenges. Learn from experienced architects about best practices, data integration, and migration in cherry-picking cloud services for optimal data platform design.

Streamline SQL Server and SSIS migration to Azure using ADF. Learn to provision SSIS-IR, run SSIS packages in ADF pipelines, and leverage DMA and DMS for efficient batch migrations.

Explore agile data warehouse modeling techniques beyond traditional norms. Learn to build flexible, auditable solutions adaptable to various industries, leveraging MDM and Azure for enhanced performance and data integration.

Explore PowerShell's versatility in managing diverse data platforms, from Excel to Azure SQL. Learn object-based data handling, code documentation, and sharing through PowerShell Notebooks for seamless integration across Microsoft data products.

Explore Azure ML's no-code approach to machine learning, from data preparation to model deployment, suitable for both beginners and experienced data scientists.

Explore improvements in Azure Data Factory for simplified data integration and management, including code-free ETL/ELT and comprehensive data overview, empowering enterprises to handle petabytes of data for valuable insights.

Explore comprehensive data quality solutions using Microsoft's Data Platform, including Machine Learning, Azure Data Factory, and SQL Server 2019, to address and resolve data quality challenges.

Discover how to leverage SQL Server 2019's memory-optimized technologies to enhance performance and scalability, taking advantage of modern hardware innovations for database applications.

Learn essential recovery techniques to prepare for, detect, and repair various corruption-based problems in databases, ensuring data integrity and minimizing disruptions in your enterprise.

Master Data Services (MDS) empowers users to manage data quality and governance. Learn how MDS integrates with Excel, enforces data standards, and streamlines operational and analytical solutions.

Discover SQL Server's Temporal Tables: automate data history tracking, simplify time-based analysis, and explore new querying syntax for efficient data management and auditing.

Learn essential database backup and restore techniques, including data files, recovery models, and automation, to safeguard your SQL Server data and prevent job-loss scenarios during disasters.

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.