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Microsoft DP-900 Exam Syllabus Topics:

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

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Microsoft Azure Data Fundamentals Sample Questions (Q229-Q234):

NEW QUESTION # 229
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

NEW QUESTION # 230
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation
Table Description automatically generated

An aggregate function performs a calculation on a set of values, and returns a single value. The following are
aggregate functions:
* APPROX_COUNT_DISTINCT
* AVG
* CHECKSUM_AGG
* COUNT
* COUNT_BIG
* GROUPING
* GROUPING_ID
* MAX
* MIN
* STDEV
* STDEVP
* STRING_AGG
* SUM
* VAR
* VARP

NEW QUESTION # 231
Which three actions are used when performing diagnostic analytics?

A. * Apply serf-learning loops to draw inferences from anomalies.
* Predict when anomalies are likely to recur
* Use analytical tools such as decision trees and regression.
B. * Identify data anomalies
* Use machine learning to find patterns in large datasets.
* Discover relationships and trends that explain anomalies.
C. * Identify data anomalies
* Predict when anomalies are likely to recur
* Use analytical tools such as decision trees and regression.
D. * Identify data anomalies
* Collect anomaly-related data
* Discover relationships and trends that explain anomalies.

Answer: D

NEW QUESTION # 232
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Reference:
https://demand-planning.com/2020/01/20/the-differences-between-descriptive-diagnostic-predictive-cognitive-analytics/

NEW QUESTION # 233
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

NEW QUESTION # 234
......

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