Term 1
Azure Blob Storage Tiers
Azure Blob Storage Tiers are pricing and performance levels that let you store data in the most cost-effective way based on how often you access it.
Acronym study
Terms 1–16 of 16 DP-203 acronyms and key terms. Each entry includes a plain-English definition and a link to the full 800-word glossary page with exam context and practice questions.
Term 1
Azure Blob Storage Tiers are pricing and performance levels that let you store data in the most cost-effective way based on how often you access it.
Term 2
Azure Data Encryption is the process of scrambling data in Microsoft Azure so that only authorized people or systems can read it.
Term 3
Azure Data Factory is a cloud-based data integration service that lets you create, schedule, and orchestrate data pipelines to move and transform data from various sources to destinations.
Term 4
Azure Data Lake Gen2 is a cloud-based data storage service that combines the scalability and performance of a data lake with the hierarchical file system and security of a data warehouse, designed for big data analytics.
Term 5
Azure Data Masking is a security feature that hides sensitive data in database query results by replacing it with obscured characters, so unauthorized users see a blurred version instead of the real information.
Term 6
Azure Data Storage Partitioning is the practice of dividing large datasets into smaller, manageable pieces called partitions to improve performance, scalability, and efficiency in cloud storage systems.
Term 7
Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure that lets data teams prepare data, run machine learning models, and build data pipelines using a single workspace.
Term 8
Azure RBAC for Data is a security system that controls who can read, write, or manage data in Azure storage services using role-based permissions.
Term 9
Azure Stream Analytics is a fully managed, real-time data processing service that analyzes and transforms high volumes of streaming data from various sources to deliver low-latency insights and trigger actions.
Term 10
Azure Synapse Analytics is a cloud-based data integration, warehousing, and analytics service that brings together big data and data warehouse capabilities under one platform.
Term 11
Azure Table Storage Design is the practice of structuring and organizing data tables in Azure’s NoSQL key-value store to ensure fast, scalable, and cost-efficient access for applications.
Term 12
Column-Level Security is a database feature that restricts access to specific columns in a table, allowing only authorized users to see sensitive data within those columns.
Term 13
Data transformation pipelines are automated sequences of steps that take raw data from a source, clean and reshape it into a usable format, and then load it into a destination for analysis or storage.
Term 14
Dynamic Data Masking is a security feature that automatically hides sensitive data in query results so that unauthorized users see only masked information, while authorized users see the real data.
Term 15
ETL and ELT are two different ways to move and transform data from source systems into a data warehouse or data lake, differing in where and when the transformation happens.
Term 16
Row-Level Security is a database feature that restricts which rows of data a user can see based on their identity or role, acting like a custom filter per person.