DP-900 Practice Exam

Create a practice exam for the MS DP-900.

MS DP-900 Practice Exam

1. Data Workloads:

   • Define "relational data."
   • What is "non-relational data"?
   • Describe "big data."

2. Azure Data Services:

   • List two features of Azure SQL Database.
   • Explain Azure Cosmos DB's consistency models.
   • Name an advantage of Azure Synapse Analytics.

3. Data Storage:

   • Differentiate between structured and unstructured data.
   • How does data lake storage work?
   • What is a data warehouse?

4. Data Processing:

   • Describe a data pipeline.
   • What is stream processing?
   • Give an example of batch processing.

5. Data Security and Compliance:

   • Explain GDPR.
   • What is role-based access control?
   • Define data encryption in transit.

Answer all questions. Time: 90 minutes.

Make it multiple choice.

MS DP-900 Practice Exam (Multiple Choice)

1. Data Workloads:

   • Define "relational data": a) Data in key-value pairs b) Data in tables with relationships c) Unstructured data d) Large datasets

   • What is "non-relational data"? a) Data in SQL format b) Data in tables without fixed schema c) Data in Excel files d) Data in structured query language

   • Describe "big data": a) Large volumes of structured data b) Large volumes of unstructured data c) Large datasets with complex patterns d) All of the above

2. Azure Data Services:

   • Two features of Azure SQL Database: a) High availability and JSON support b) NoSQL support and machine learning c) Data lake integration and XML support d) In-memory computing and graph database

   • Azure Cosmos DB's consistency models include: a) Eventual and strong consistency b) Immediate and delayed consistency c) Local and global consistency d) Sequential and parallel consistency

   • An advantage of Azure Synapse Analytics: a) Real-time analytics b) Automatic data cleaning c) Inbuilt AI capabilities d) Native graph processing

3. Data Storage:

   • Structured vs. unstructured data: a) Structured is more flexible b) Unstructured has a pre-defined model c) Structured is in tabular form d) Unstructured cannot be stored digitally

   • Data lake storage: a) Stores structured data only b) Optimized for large files c) Primarily for transactional data d) Same as traditional databases

   • What is a data warehouse? a) For real-time data processing b) Optimized for writing data c) Designed for analytical processing d) Only for unstructured data

4. Data Processing:

   • A data pipeline: a) Is a static data model b) Moves and transforms data c) Processes data in real-time only d) Is used only for small datasets

   • Stream processing: a) Handles data in batches b) Processes data as it arrives c) Is less efficient than batch processing d) Only for audio and video streams

   • Example of batch processing: a) Sensor data analysis b) E-commerce transactions c) Nightly inventory updates d) Social media feeds

5. Data Security and Compliance:

   • GDPR is about: a) Global data placement rules b) European data protection c) General data processing regulations d) Government data privacy regulations

   • Role-based access control: a) Assigns permissions based on job function b) Encrypts data at rest c) Monitors network traffic d) Is a firewall feature

   • Data encryption in transit: a) Encrypts data being moved b) Encrypts data being deleted c) Stores data in encrypted format d) Encrypts only emails

Answer all questions. Time: 90 minutes.