
Explore Azure SQL Database migrations, including challenges, limits, and best practices for new projects, instrumentation, web apps, parallel processing, and data warehousing.

Explore temporal tables in SQL Server, their functionality, and applications in ETL and data warehousing. Learn implementation, querying techniques, and considerations for effective use.

Learn to build mission-critical apps using SQL Server 2017's advanced features like In-Memory performance, Automatic Tuning, and Always Encrypted for enhanced security and efficiency.

Explore Azure's big data and MPP offerings, including data lakes, HDInsight, and SQL Data Warehouse. Learn about architecture, storage options, and processing capabilities for efficient data management.

Explore big data architectures, data lakes, and modern data warehousing. Learn about Hadoop, cloud benefits, and strategies to effectively manage and analyze large-scale data for business intelligence.

Discover resources, best practices, and solutions for migrating big data to Azure. Learn about ADLS Gen2, Azure SQL Data Warehouse, and data movement tools for successful petabyte-scale transfers.

Learn to evaluate, provision, and optimize Azure SQL Data Warehouse. Covers scalability, cost-effectiveness, data loading, performance improvement, and security best practices for cloud-based data warehousing.

Meet Microsoft's Data Engineering team, discuss SQL Server, Azure SQL, and data services. Gain insights into product development, engineering processes, and future plans. Engage directly with PMs in this interactive session.

Discover Snowflake's cloud data warehouse: simplified management, scalable performance, and cost-effectiveness. Learn about its multi-cluster architecture, resource separation, and easy implementation for efficient data handling.

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 rapid data modeling and prototyping using Power BI Desktop. Learn to connect, cleanse, and model data from various sources, creating quick reports for project approval without licensing costs.

Explore recent enhancements to Columnstore Indexes in SQL Server 2017-2019, focusing on performance improvements for Data Warehouses and BI solutions. Learn about new features and fixes for high-scale environments.

Explore high-performance data analysis using Power BI Aggregations. Compare with Analysis Services, learn implementation strategies, and understand architectural approaches for optimized analytical solutions.

Explore Azure Synapse Analytics, a comprehensive platform integrating relational and big data systems for efficient data ingestion, preparation, modeling, and serving in a unified workspace.

Explore cloud-based data warehousing options, comparing Snowflake, Databricks, and Azure solutions. Learn to choose the best fit for your environment based on size, architecture, and unique features.

Explore Azure Synapse Analytics, a unified service combining data warehousing and Big Data analytics. Learn about its features, scalability, and integration in modern data warehouses through demonstrations.

Explore cloud data warehousing solutions, comparing Snowflake, Synapse, Redshift, and BigQuery. Learn key principles, features, and how these platforms revolutionize data management and analysis.

Explore Polybase, Microsoft's linked server replacement, for connecting to diverse data sources. Learn setup best practices, scale-out groups, AlwaysOn integration, and performance optimization techniques.

Explore agile data warehouse development using Data Vault design and metadata-driven automation for faster delivery, flexible architecture, and improved documentation in business intelligence projects.

Explore NYC bike share trends using BigQuery to analyze 33 million trips. Learn to query, visualize, and interpret data for insights on popular routes and rider demographics.

Explore NYC bike share trends using BigQuery to analyze 33 million trips. Learn to query and visualize big data, with applications for various datasets including Australian and Github data.