
Explore data virtualization using SQL Server 2019 Big Data Cluster. Learn to access and analyze external data sources, implement data ingestion, and gain insights from a real project's lessons learned.

Explore evolving analytics trends, skills, and technologies for business analysts. Learn to work with data science, improve data literacy, and embrace ambiguity in modern business intelligence.

Explore the power of middle-tier modeling and calculation layers in data analysis, challenging the traditional "storage and charts" approach with case studies and clear explanations of their value.

Explore Azure's data movement and transformation options, comparing SSIS with Data Factory, Databricks, and Logic Apps. Learn ETL patterns and Data Flow features for scalable cloud migration.

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.

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.

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

Automate ETL processes using BIMLScript and metadata to easily adapt to source file changes, demonstrated with US census data and applicable to SSIS and Azure Data Factory.

Explore SQL Server 2019's Big Data Clusters, combining open-source technologies with SQL Server for advanced analytics. Learn how containers and Kubernetes integrate Apache Spark, Hadoop, and SQL Server into a unified analytics solution.

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

Comprehensive Python data modeling tutorial covering extraction, cleaning, transformation, visualization, predictive modeling, validation, and deployment using popular libraries and Azure integration.

Discover game-changing Excel tools for data-driven decisions. Learn multi-source import, rapid data shaping, portable formulas, and insightful reporting techniques to supercharge your spreadsheet skills.

Explore data visualization ethics, examining how color and chart choices influence storytelling. Learn to create truthful, impactful visualizations while protecting your company's reputation.

Advanced techniques for effective data visualization, including accessibility design, data storytelling, and creating impactful reports and dashboards for diverse audiences.

Learn to set up an inexpensive system using Telegraf, InfluxDB, and Grafana to collect and visualize SQL Server performance metrics, aiding in troubleshooting and capacity planning.

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 Charticulator, an open-source tool for creating stunning Power BI custom visuals without coding. Learn to enhance your data visualization capabilities and unlock new possibilities in data presentation.

Explore strategies for integrating Business Intelligence into your organization, including infrastructure configuration, leveraging Power Platform, and addressing key challenges and opportunities.

Explore PowerApps and AI integration for location tracking, using Bing maps, Azure SQL, and Cognitive Services. Learn to create mobile apps with real-time alerts and location-aware web searches.

Learn to analyze text data using Azure Cognitive Services and Power BI. Extract key phrases, derive sentiment scores, and create effective visual dashboards without needing advanced data science skills.

Explore hybrid SQL-NoSQL solutions, focusing on integrating MongoDB with SQL Server. Learn scenarios, implementation techniques, and performance considerations for leveraging strengths of both database types.