Data is the foundation on which all software is built. By learning about common data formats, workloads, roles, and services, you can prepare yourself for a career as a data professional. This learning path helps you prepare for the Azure Data Fundamentals certification.

The phenomenal growth in data in recent years is fueling digital transformation of businesses and other organizations by empowering fast and informed decision making through data analytics. Microsoft Azure provides multiple services that you can combine to build large-scale analytics solutions that leverage the latest technologies and techniques for data ingestion, storage, modeling, and visualization. This learning path helps you prepare for the Azure Data Fundamentals certification.

Non-relational data is a common way for applications to store and query data without the overhead of a relational schema. In Microsoft Azure, you can use Azure Storage and Azure Cosmos DB to build highly scalable, secure data stores for non-relational data. This learning path helps you prepare for the Azure Data Fundamentals

Relational data is at the heart of most business applications, and is the foundation on which many enterprise data solutions are built. Microsoft Azure provides services for managing relational databases, enabling you to build new applications or migrate existing ones to the cloud. This learning path helps you prepare for the Azure Data Fundamentals

How can you use a Fabric workspace to query Azure Data Lake for analytics? This course will teach you how to use SQL and a query designer to extract data through lakehouse and warehouse artifacts in Fabric, and will help you pass the DP-600 exam.

Designing scalable and performant semantic models is one of the key requirements in enterprise-grade environments. This course will teach you how to implement and manage optimal semantic models to support efficient business decision-making.

This course will teach you the skills needed to plan, implement, and manage a Microsoft Fabric solution for data analytics in the age of AI.

With more and more data in existence, the field of analytics is becoming more and more challenging. Microsoft Fabric provides an end-to-end solution for all your analytics needs - from storing your data to reporting and governance.

Discover strategies for mitigating disasters in machine learning pipelines, focusing on best practices for monitoring, validation, and error handling.

Learn what a Power BI semantic model is, which data loading approach to use, and how to build out your semantic model to get the insights you need.

Learn how to work with data that comes from different sources and is structured in different ways by using Power BI transformations to combine, reshape, cleanse, and enhance that data to create a model that supports reporting and analytics.

Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.