Plan an appropriate high availability and disaster recovery strategy based on recovery time objective and recovery point objective. Choose the best solution for IaaS or PaaS deployments or hybrid workloads.

Compare Azure, and on-premises tools for monitoring and measuring performance. Determine critical metrics. Understand the purpose of a baseline for comparative analysis. Configure extended event sessions for tracing activities.

Learn how to design a data ingestion solution for training data used in machine learning projects.

Learn how to design a model training solution for machine learning projects.

Learn about machine learning operations or MLOps to bring a model from development to production. Identify options for monitoring and retraining when preparing a model for production.

There are many options on Azure to train and consume machine learning models. Which service best fits your scenario can depend on a myriad of factors. Learn how to identify important requirements and when to use which service when you want to use machine learning models.

Learn how to design a model deployment solution and how the requirements of the deployed model can affect the way you train a model.

This course will teach you how to design a data model with Power BI.

The use of OneDrive, Git repositories, and Power BI deployment pipelines allows us to follow application lifecycle management techniques. This reduces administrative overhead and provides continuity in the development process.

The process of creating a complicated semantic model in Power BI is straightforward. If your data is coming in from more than one transactional system, before you know it, you can have dozens of tables that you have to work with. Building a great semantic model is about simplifying the disarray. A star schema is one way to simplify a semantic model, and you learn about the terminology and implementation of them in this module. You will also learn about why choosing the correct data granularity is important for performance and usability of your Power BI reports. Finally, you learn about improving performance with your Power BI semantic models.

This learning path introduces the foundational components of designing scalable tabular models using Power BI. This learning path helps you prepare for the Azure Enterprise Data Analyst Certification.

Learn how to query SQL databases and design relational databases to efficiently store large quantities of data.