Title: Detailed DP-900 Study Plan - Valid DP-900 Study Materials [Print This Page] Author: harrywa582 Time: 12 hour before Title: Detailed DP-900 Study Plan - Valid DP-900 Study Materials P.S. Free 2026 Microsoft DP-900 dumps are available on Google Drive shared by ExamTorrent: https://drive.google.com/open?id=1XRtJHA0KfhwCj2KuT_NY-OAVmn0drY10
In the PDF version, real DP-900 exam questions are available. These Microsoft DP-900 real questions are printable and portable. You can take this PDF document anywhere and study for the Microsoft Azure Data Fundamentals (DP-900) exam without time restrictions. ExamTorrent regularly make changes in the DP-900 PDF format when required. DP-900 questions in this format are relevant to the actual test.
Microsoft DP-900 exam is an entry-level certification that is suitable for professionals who are new to the world of data management and analytics on the cloud. DP-900 exam is not only limited to technical professionals, but also business professionals who want to gain a better understanding of the Azure cloud platform and its data management capabilities. Microsoft Azure Data Fundamentals certification is also valuable for students who are interested in pursuing a career in data science or cloud computing. By passing the DP-900 Exam, candidates can demonstrate their foundational knowledge and understanding of Azure data services to potential employers, which can lead to greater job opportunities and career advancement.
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Your company plans to load data from a customer relationship management (CRM) system to a data warehouse by using an extract load, and transform (ELT) process.
Where does data processing occur for each stage of the ELT process? To answer, drag the appropriate locations to the correct. Each location may be used once, or not at all, You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point. Answer:
Explanation:
Explanation:
Box 1: The CRM system
Data is extracted from the CRM system.
Box 2: The data warehouse
Data is loaded to the data warehouse.
Box 3: An in-memory data integration tool
The data transformation that takes place usually involves various operations, such as filtering, sorting, aggregating, joining data, cleaning data, deduplicating, and validating data.
NEW QUESTION # 147
When provisioning an Azure Cosmos DB account, which feature provides redundancy within an Azure region?
A. Availability Zones
B. automatic failover
C. the strong consistency level
D. multi-master replication
Answer: A
Explanation:
Explanation
With Availability Zone (AZ) support, Azure Cosmos DB will ensure replicas are placed across multiple zones within a given region to provide high availability and resiliency to zonal failures.
Note: Azure Cosmos DB provides high availability in two primary ways. First, Azure Cosmos DB replicates data across regions configured within a Cosmos account. Second, Azure Cosmos DB maintains 4 replicas of data within a region.
NEW QUESTION # 148
To complete the sentence, select the appropriate option in the answer area. Answer:
Explanation:
NEW QUESTION # 149
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 # 150
Which three actions are used when performing diagnostic analytics?
A. * Identify data anomalies
* Collect anomaly-related data
* Discover relationships and trends that explain anomalies.
B. * Identify data anomalies
* Predict when anomalies are likely to recur
* Use analytical tools such as decision trees and regression.
C. * 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.
Answer: A
Explanation:
D.
* Identify data anomalies
* Use machine learning to find patterns in large datasets.
* Discover relationships and trends that explain anomalies.
NEW QUESTION # 151
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