About This Course
As a data pro, you know that some scenarios—particularly those involving real-time analytics, site personalization, IoT, and mobile apps—are better addressed with NoSQL storage and compute solutions than they are with relational databases. Microsoft Azure has several NoSQL (or “Not Only SQL”) non-relational data storage options to choose from. NoSQL databases are generally built to be distributed and partitioned across many servers. And they’re built to scale out for high availability and to be flexible enough to handle semi-structured and unstructured data. If you have a data model that is constantly evolving and you want to move fast, that’s what these databases are about.
In this practical course, complete with labs, assessments, and a final exam, join the experts to learn how NoSQL has evolved over time. Explore non-relational data storage options in Azure, and see how to use them in your applications. Find out how to create, store, manage, and access data in these different storage options. Get an in-depth look at Azure Table Storage, DocumentDB, MongoDB, and more. Learn about the “three Vs”—variety (schemas or scenarios that evolve quickly), volume (scale in terms of data storage), and velocity (throughput needs to support a large user base). Take this opportunity to get hands-on with NoSQL options in Azure.
- Relational Database Fundamentals
- T-SQL Querying
- Basic understanding of HTTP APIs and Requests
What you'll learn
- NoSQL fundamentals
- Overview of NoSQL options in Azure Cosmos DB
- Fundamental techniques for using the DocumentDB API, Tables API, and MongoDB API
- Other techniques for accessing and improving performance of your NoSQL storage
Meet the instructor
Senior Content Developer
Microsoft’s Learning Experiences
Pete Harris is a Senior Content Developer in Microsoft’s Learning Experiences team based in Redmond, WA. He has a diverse background building content that spans Microsoft’s application platform including Microsoft Azure and various data platform services. Pete has been building content for Microsoft since 1995. He continues to meet customers who think he looks familiar from training videos they saw of him in the Mastering Series titles he worked on in the nineties as well as current training on MicrosoftVirtualAcademy.com.
Microsoft Certified Trainer, Cloud Applications Consultant
Sidney Andrews is a Microsoft Certified Trainer and Azure MVP with SeeSharpRun.NET. He has a background in ASP.NET web development, along with extensive experience developing applications using XAML. Sidney has driven efforts to develop and deliver Azure readiness training through channels such as Ignite, Microsoft Tech Summit, Microsoft Virtual Academy, Microsoft Official Courseware, internal Microsoft training and even public whitepapers. Sidney also leads efforts to open-source traditional classroom training for Azure using GitHub.
Andrew Liu is a program manager working on Microsoft's Azure Cosmos DB team. He's passionate about enabling developers and businesses to deliver new experiences through a novel globally distributed NoSQL database service. Prior to joining Microsoft, Andrew worked as software engineer building mission-critical infrastructure for one of the world's largest e-commerce websites. In his spare time, he enjoys geeking out over web crawlers, video games, and whiskeys.
I am a Data Scientist and trainer at Microsoft where I share my Python, R and advanced analytics experience internally and externally. I have led or co-led workshops around data science and analytics concepts in Python and R, often utilizing Jupyter notebooks for interactive coding. I have developed a “Python for the Data Scientist” course delivered on Jupyter notebooks and have delivered this at Microsoft several times and look forward to its external release. I've also delivered courses utilizing Microsoft Azure and covering DocumentDB, Cognitive Services, the Bot Framework, as well as other components of the Cortana Intelligence Suite. I enjoy teaching/training and finding the most effective ways to teach data science and advanced analytics on any size dataset.