To learn about resources for gathering data from multiple sources and how to and apply data transformations within the data pipeline, see Extract, transform, and load (ETL).To find options helpful for dealing with relational data, consider these resources: Explore Azure database and analytics services.
Choose a data storage approach in Azure.Here are some Learn modules you might find useful: You can browse Azure data modules or use this learning path to understand Azure SQL fundamentals. Microsoft Learn offers learning paths that are based on your job role, such as developer or data analyst. This free online platform provides videos and tutorials for hands-on learning. If you're new to databases on Azure, the best place to start is Microsoft Learn. We also provide solution ideas for you to build on, which include links to all the components you need. There are many architectures for you to draw from to address your database needs. It outlines paths to implement the architectures that meet your needs, and best practices to keep in mind as you design your solutions. This article provides resources to learn about Azure databases. This type of database is referred to as NoSQL (not only SQL). You can use an extract, transform, and load (ETL) process to move and transform the source data.Ī big data architecture is designed to handle the ingestion, processing, and analysis of large or complex data.īig data solutions typically involve a large amount of non-relational data, which traditional RDBMS systems aren't well suited to store. RDBMS workloads include online transaction processing (OLTP) and online analytical processing (OLAP).ĭata from multiple sources in the organization can be consolidated into a data warehouse. This article provides an overview of the Azure database solutions described in Azure Architecture Center.Īzure Database solutions include both traditional relational database management system (RDBMS) and big data solutions.
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