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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Non-Relational Data in Azure | 15-20% | - Data processing options for non-relational data - Azure storage services
|
| Topic 2: Relational Data in Azure | 20-25% | - Azure relational data services
- Relational data concepts |
| Topic 3: Core Data Concepts | 25-30% | - Relational vs non-relational data - Roles and responsibilities in data work - Data analytics workloads overview - Types of core data workloads |
| Topic 4: Analytics Workloads in Azure | 25-30% | - Data analytics concepts - Data visualization and reporting - Data ingestion and processing - Azure analytics services
|
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NEW QUESTION # 312
Drag and Drop Question
Match the data processing languages to the appropriate real-time analytics services.
To answer, drag the appropriate term from the column on the left to its description on the right.
Each term may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
Explanation:
Azure Data Explorer: KQL (Kusto Query Language), which is a proprietary query language specifically designed for Azure Data Explorer. It is used to analyze and query large volumes of structured and unstructured data in real-time.
Azure Stream Analytics: SQL, which is a standard query language for relational databases. It is used to analyze and process high-velocity, real-time streaming data from various sources, such as IoT devices, social media platforms, and other real-time data streams.
Azure Synapse Analytics: SQL and Python. SQL is used to query and analyze structured data stored in Azure Synapse Analytics, while Python can be used for data preprocessing, machine learning, and other data science tasks.
NEW QUESTION # 313
Match the Azure services to the appropriate requirements.
To answer, drag the appropriate service from the column on the left to its requirement on the right. Each service may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/supported-file-formats-and-compression-codecs
NEW QUESTION # 314
What are three characteristics of an Online Transaction Processing (OLTP) workload? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: B,C,D
Explanation:
B: Typical traits of transactional data include: schema on write, strongly enforced. The schema is defined in a database.
D: Transactional data tends to be highly normalized.
F: Transactional data tends to be heavy writes, moderate reads.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/online-transaction- processing
NEW QUESTION # 315
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: No
Microsoft handles all patching and updating of the SQL and operating system code. You don't have to manage the underlying infrastructure.
Box 2: Yes
SQL Database is a fully managed service that has built-in high availability, backups, and other common maintenance operations.
Box 3: No
NEW QUESTION # 316
Match the security components to the appropriate scenarios.
To answer, drag the appropriate component from the column on the left to its scenario on the right. Each component may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
NEW QUESTION # 317
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