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Microsoft DP-900 Exam Syllabus Topics:

Section	Weight	Objectives
Describe an analytics workload on Azure	25–30%	- Describe Azure analytics services 1. Azure Databricks 2. Azure HDInsight 3. Azure Synapse Analytics 4. Azure Data Lake Storage Gen2 5. Microsoft Fabric - Describe data visualization 1. Power BI capabilities 2. Data models and reports - Describe big data and analytics concepts 1. Data lakes and data warehouses 2. Data ingestion and processing 3. Modern data warehouse architecture - Describe real-time analytics 1. Stream processing concepts 2. Azure Stream Analytics
Describe considerations for working with non-relational data on Azure	15–20%	- Describe Azure Cosmos DB 1. APIs and data models 2. Capabilities and features 3. Consistency levels and partitioning - Describe non-relational data concepts 1. Characteristics of NoSQL data 2. Use cases for non-relational data - Describe Azure storage services 1. Blob Storage 2. File Storage 3. Table Storage 4. Queue Storage
Describe core data concepts	25–30%	- Describe roles and responsibilities 1. Data engineer, data analyst, database administrator - Describe types of data 1. File formats 2. Structured, semi-structured, and unstructured data - Describe data workloads 1. Transactional workloads 2. Batch and streaming data 3. Analytical workloads
Identify considerations for relational data on Azure	20–25%	- Describe Azure relational data services 1. Azure SQL Database 2. Azure SQL Managed Instance 3. Open-source databases: PostgreSQL, MySQL, MariaDB 4. SQL Server on Azure Virtual Machines - Describe relational data concepts 1. Query data with SQL 2. Normalization 3. Relationships, keys, constraints

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Microsoft Azure Data Fundamentals Sample Questions (Q37-Q42):

NEW QUESTION # 37
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation:

Generally speaking, data analytics comes in four types (Figure 1):
Descriptive, to answer the question: What's happening?
Diagnostic, to answer the question: Why's happening?
Predictive, to answer the question: What will happen?
Prescriptive, to answer the question: What actions should we take?
Reference:
https://azure.microsoft.com/en-us/blog/answering-whats-happening-whys-happe ning-and-what-will-happen-with-iot-analytics/

NEW QUESTION # 38
Which type of database contains nodes and edges?

A. graph
B. columnar
C. time series
D. key/value

Answer: A

NEW QUESTION # 39
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: Yes
Azure Databricks can consume data from SQL Databases using JDBC and from SQL Databases using the Apache Spark connector.
The Apache Spark connector for Azure SQL Database and SQL Server enables these databases to act as input data sources and output data sinks for Apache Spark jobs.
Box 2: Yes
You can stream data into Azure Databricks using Event Hubs.
Box 3: Yes
You can run Spark jobs with data stored in Azure Cosmos DB using the Cosmos DB Spark connector.
Cosmos can be used for batch and stream processing, and as a serving layer for low latency access.
You can use the connector with Azure Databricks or Azure HDInsight, which provide managed Spark clusters on Azure.

NEW QUESTION # 40
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/create-graph-gremlin-console

NEW QUESTION # 41
Select the answer that correctly completes the sentence.

Answer:

Explanation:

NEW QUESTION # 42
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