About This Course
This course is part of the Microsoft Professional Program Certificate in Big Data.
If you’re familiar with NoSQL in Azure and the platform’s powerful non-relational data storage options, take the next step! Join us for an in-depth look at developing NoSQL apps in super-scalable Azure Cosmos DB—the distributed, multi-model database from Microsoft that transparently replicates your data wherever your users are. Learn about its broad, global-scale features and capabilities. Then, go deeper into some of the APIs available in Azure Cosmos DB for storing different kinds of NoSQL data.
We'll start with a look at general concepts, including partitioning schemes, global replications, hierarchy, security, and more, as you learn to develop document, key/value, or graph databases with Cosmos DB using a series of popular APIs and programming models.
Plus, we'll work with API specifics for DocumentDB, Gremlin, MongoDB, and Tables and conclude with a look at real-world integrations, visualizations, and analyses, such as Spark Connector, Azure Search, Stream Analytics.
Meet the instructors
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.
Principal Program Manager
Denny Lee is a Principal Program Manager at Microsoft for the Azure Cosmos DB team - Microsoft's globally distributed, multi-model database. He is a hands-on distributed systems and data sciences engineer with extensive experience developing internet-scale infrastructure, data platforms, and predictive analytics systems for both on-premise and cloud environments. Prior to joining the Azure Cosmos DB team, Denny worked as a Technology Evangelist at Databricks; he has been working with Apache Spark since 0.5. He was also the Senior Director of Data Sciences Engineering at Concur, and was on the incubation team that built Microsoft's Hadoop on Windows and Azure service (currently known as HDInsight). Denny also has a Masters of Biomedical Informatics from Oregon Health and Sciences University.
Principal Program Manager
Govind Kanshi works in Microsoft’s Azure Cosmos DB team to help customers adopt the product in pragmatic way. In his previous experience he has enjoyed roles across support, engineering and software architecture to help customers across various industries. His specialization remains in databases and application middle tier design and development. He has specific experience with fraud analytics in government subsidies and electoral rolls. He has been helping ISVs adopt cloud services from the early days of the cloud.