
Optimize database performance by understanding ORM frameworks, LINQ, and application impact. Learn to improve queries, enhance developer collaboration, and boost your value as a data professional.

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.

Introduction to Azure's Computer Vision and Custom Vision APIs, covering basics, model creation, training, and implementation using Python in Azure Notebooks.

Learn to develop extensions for Azure Data Studio using Typescript, exploring APIs, GitHub hosting, and marketplace sharing. Gain practical skills through a live demonstration of building a functional extension.

Learn Python basics, data manipulation, and integration with Microsoft tools for enhanced data analytics and machine learning capabilities.

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

Learn to harness PySpark for big data analytics, covering RDDs, DataFrames, transformations, and machine learning. Gain practical skills for efficient data processing and analysis using Python and Spark.

Explore AI, ML, and DL with Buck Woody: learn key differences, use-cases, and implementation options, including SQL Server platform technologies.

Learn to automate SQL deployments and upgrades using PowerShell, starting with basics and progressing to multi-server scripts using JSON files.

Explore strategies to mitigate ORM-related issues, improve performance, and satisfy both developers and DBAs. Learn to audit SQL, optimize code, and use tools for better ORM implementation.

Transition SQL Server skills to CosmosDB: Learn NoSQL concepts, JSON, multi-models, and key differences in monitoring and data structure. Prepare for a new approach to database management and optimization.

Explore SQL Server's evolution from Docker support to Big Data Clusters, covering containerization, Kubernetes deployment, and integration with Python for modernized database management and analytics.

Explore Azure SQL's capabilities for building high-performance, scalable REST APIs with JSON support, CI/CD integration, and robust security features for modern agile development.

Strategies for efficient data retrieval from SQL Server, comparing methods like stored procedures and ORMs. Includes implementation examples in .NET and tips for performance tuning and database structuring.

Discover advanced Power BI automation techniques using CLI, PowerShell, and C#. Learn to streamline administration tasks, implement continuous integration, and create artifacts automatically.

Comprehensive introduction to Python for data science, covering basics and machine learning using real-world datasets. Ideal for beginners looking to integrate Python into Microsoft tools.

Accelerate your Python journey as a SQL expert with practical code examples, skipping frustrations, and gaining inspiration for further learning and immediate application in daily work.

Explore x86_64 LLVM Linux project updates, current issues, and strategies for upstreaming work into the Linux Kernel or LLVM/Clang, with a focus on resolving challenges and accelerating progress.

Explore gcc extension VLAIS in Linux Kernel, its issues, alternatives, and plans for removal. Gain insights into compiler compatibility and kernel development challenges.

Exploring LLVM adoption for Hexagon DSP, covering Linux kernel and user space compilation challenges, solutions, and ongoing issues in replacing GCC with LLVM toolchain.

Explore Intel TSX implementation for lock elision in Linux, covering kernel, glibc, and other components to address lock scaling challenges in multi-CPU systems.