Azure Data Fundamentals Free Sample Questions

This is the optimal solution. Azure Cosmos DB is excellent for storing and querying structured (demographics) and semi-structured (text notes) data in a single document per patient, offering fast retrieval. Azure Blob Storage is the most cost-effective and performant service for storing large binary files like medical images (unstructured data). The Cosmos DB record can simply store a URI pointing to the image in Blob Storage.

DAX time intelligence functions, such as SAMEPERIODLASTYEAR, PREVIOUSMONTH, or TOTALYTD, are specifically designed to simplify and perform common time-based comparisons and calculations. Using these functions is the standard and most efficient way to compare data across different time periods in Power BI.

Parquet is a columnar storage format that is highly optimized for analytical workloads. It offers excellent compression, which reduces storage costs and improves query performance. Crucially, it supports schema evolution, allowing you to add, remove, or modify columns over time without breaking existing data pipelines. It is the preferred format for large-scale analytics in services like Azure Synapse and Databricks.

This statement is false. In OLTP systems, data is typically normalized (e.g., to Third Normal Form) to reduce data redundancy, prevent data modification anomalies, and ensure data integrity for frequent write operations (inserts, updates, deletes). Denormalization is a technique used in Online Analytical Processing (OLAP) systems or data warehouses to optimize read performance for complex queries by intentionally adding redundant data.

Azure Cosmos DB is a globally distributed, multi-model database service designed for low-latency (single-digit millisecond) reads and writes at any scale. Its key feature is turnkey global distribution, which allows you to replicate data to any Azure region and configure any region as a writable endpoint. This makes it the ideal choice for applications with a global user base requiring high availability and performance.

The responsibilities described—building and maintaining data pipelines, performing ETL/ELT operations, and ensuring data quality—are core functions of a Data Engineer. Data Engineers focus on the infrastructure and processes for moving and transforming data to make it available for analysis.

Azure Files is the service specifically designed to provide fully managed cloud file shares accessible via the industry-standard Server Message Block (SMB) and Network File System (NFS) protocols. This makes it ideal for migrating existing applications and workloads that rely on on-premises file servers, as it allows mounting the share just like a local network drive.

The GRANT statement is part of Data Control Language (DCL) and is used to give specific permissions, such as SELECT (read), to a user or role.

The SELECT statement is part of Data Manipulation Language (DML) and is the permission that allows a user to read or query data from a table. The administrator would use GRANT SELECT to achieve the goal.

In an ELT (Extract, Load, Transform) process, raw data is first extracted from the source and loaded directly into the target data store (like Azure Synapse Analytics). The powerful processing capabilities of the target system are then used to perform the transformations in place. This contrasts with ETL, where transformation happens in a separate staging area before the data is loaded into the target.

Azure SQL Managed Instance is specifically designed for this scenario. It is a fully managed PaaS offering that provides near-100% compatibility with the latest on-premises SQL Server Enterprise Edition database engine. It supports instance-level features like SQL Server Agent, Service Broker, and cross-database queries, making it the ideal choice for migrating existing SQL Server applications with minimal changes.