Candidates for this exam should have foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services. This exam is intended for candidates beginning to work with data in the cloud. Candidates should be familiar with the concepts of relational and non-relational data, and different types of data workloads such as transactional or analytical. Azure Data Fundamentals can be used to prepare for other Azure role-based certifications like Azure Database Administrator Associate or Azure Data Engineer Associate, but its not a prerequisite for any of them. Prove that you can describe the following: core data concepts; how to work with relational data on Azure; how to work with non-relational data on Azure; and an analytics workload on Azure. Skills measuredDescribe core data concepts (15-20%)describe batch datadescribe streaming datadescribe the difference between batch and streaming datadescribe the characteristics of relational dataDescribe how to work with relational data on Azure (25-30%)describe data visualization (e.g, visualization, reporting, business intelligence (BI))describe basic chart types such as bar charts and pie chartsdescribe analytics techniques (e.g, descriptive, diagnostic, predictive, prescriptive, cognitive)describe ELT and ETL processingdescribe the concepts of data processingDescribe how to work with non-relational data on Azure (25-30%)Describe relational data workloadsidentify the right data offering for a relational workloaddescribe relational data structures (e.g, tables, index, views)Describe relational Azure data servicesdescribe and compare PaaS, IaaS, and SaaS solutionsdescribe Azure SQL family of products including Azure SQL Database, Azure SQL Managed Instance, and SQL Server on Azure Virtual Machinesdescribe Azure Synapse Analyticsdescribe Azure Database for PostgreSQL, Azure Database for MariaDB, and Azure Database for MySQLDescribe an analytics workload on Azure (25-30%)Describe analytics workloadsdescribe transactional workloadsdescribe the difference between a transactional and an analytics workloaddescribe the difference between batch and real timedescribe data warehousing workloadsdetermine when a data warehouse solution is neededDescribe the components of a modern data warehousedescribe Azure data services for modern data warehousing such as Azure Data Lake Storage Gen2, Azure Synapse Analytics, Azure Databricks, and Azure HDInsightdescribe modern data warehousing architecture and workloadDescribe data ingestion and processing on Azuredescribe common practices for data loadingdescribe the components of Azure Data Factory (e.g, pipeline, activities, etc.)describe data processing options (e.g, Azure HDInsight, Azure Databricks, Azure Synapse Analytics, Azure Data Factory)Good Luck!
