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The official Microsoft Certified: Azure Data Fundamentals syllabus, organized by domain. Check off each point as you review it.
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Describe ways to represent data
Structured data adheres to a fixed schema, so every instance of an entity has the same fields. It is most commonly represented in tables: rows are the instances and columns are the attributes, and each column stores a specific datatype. It is often stored in relational databases, where tables are linked through keys.
Identify data formats - Training ↗Understand relational data - Training ↗
Semi-structured data has some structure but allows variation between instances: for example, one customer may have several email addresses and another none. JSON is a very common format, with a hierarchical schema where an attribute can be an object or a collection. JSON is only one possible representation, and document databases store JSON documents.
Identify data formats - Training ↗Explore file storage - Training ↗
Unstructured data has no specific structure: documents, images, audio, video and binary files. It is stored as raw binary that applications must interpret, and data professionals call such files BLOBs. Azure Blob Storage is optimized for storing massive amounts of this kind of data. Vector data (embeddings) lets AI answer questions over it.
Identify data formats - Training ↗Introduction to Blob (object) Storage - Azure Storage ↗
Identify options for data storage
The file format depends on the type of data, the applications that use it and whether it must be human-readable or optimized. Delimited text (CSV, TSV, fixed-width) suits structured data; JSON suits structured and semi-structured data; XML is readable but more verbose. Parquet (columnar) and Avro (row-based) compress and process better, and Delta Lake adds transactions on top of Parquet.
A database is a dedicated system for managing data records, not just files. Relational databases keep structured data in tables with primary keys, normalized and queried with SQL. Nonrelational databases, often called NoSQL, do not apply a relational schema: key-value, document, column family and graph. No single store fits everything, so models are often combined.
Explore databases - Training ↗Understand Data Models - Azure Architecture Center ↗
Each need has its datastore: Azure Blob Storage holds unstructured data (images, video, backups) and, with a hierarchical namespace, forms the data lake; Azure Files offers SMB/NFS file shares; Azure Table storage keeps schemaless key/attribute data; Azure Cosmos DB is the low-latency global NoSQL database; and the Azure SQL family covers relational data.
Introduction to Azure Storage - Cloud storage on Azure ↗What Is Azure SQL? ↗
Describe common data workloads
A transactional (OLTP) workload records business events as small, fast units of work, mostly writes with moderate reads, and supports line of business applications. It applies CRUD operations with ACID semantics: atomicity, consistency, isolation and durability. Its data is typically highly normalized with an enforced schema.
Explore transactional data processing ↗Online Transaction Processing (OLTP) ↗
An analytical workload uses read-only or read-mostly systems holding large volumes of historical data. Data is loaded with ETL or ELT into a data lake, lakehouse or data warehouse, and can be aggregated into an OLAP or semantic model for reports and dashboards. Microsoft Fabric and Azure Databricks are modern analytics platforms.
Explore analytical data processing ↗Online Analytical Processing ↗
Identify roles and responsibilities for data workloads
The database administrator designs, implements and maintains on-premises and cloud-based database systems. They ensure availability, performance and optimization, define backup and recovery plans, and manage security by granting or denying access. With PaaS services such as Azure SQL Database they no longer manage the engine, operating system or hardware.
Explore job roles in the world of data ↗What Is Azure SQL? ↗
The data engineer designs and implements ingestion pipelines, cleansing and transformation activities, and data stores for analytical workloads. They manage and monitor pipelines, maintain data privacy between on-premises and cloud, and work with tools such as Azure Data Factory, Microsoft Fabric, Azure Databricks, Azure Stream Analytics and Microsoft Purview.
Explore job roles in the world of data ↗Identify data services ↗
A data analyst explores data to identify trends and relationships, designs analytical models and turns raw data into insights through reports and visualizations, based on business requirements. Analysts typically use Power BI. The role differs from the database administrator (permissions, backups) and the data engineer (pipelines, cleansing), and one person can hold several roles.
Explore job roles in the world of data - Training ↗Identify data services - Training ↗