Data Engineering on Microsoft Azure
- Product Code: dp-203
- Exam Questions: 317
- Vendor: microsoft
$9.99
$12.99- Updated At: Nov 14, 2024
DA-100: Microsoft Data Analytics with Azure
Validate your skills in designing, implementing, and managing data engineering solutions on Microsoft Azure.
Focus
The Data Engineering on Microsoft Azure certification focuses on Data Engineering with Microsoft Azure
Exam Duration
The Data Engineering on Microsoft Azure exam duration is 150 minutes
Num of Question
The exam contains a total of 49
Exam Fee
The exam fee is $165.
Exam Validity
The CCRN-Pediatric certification is valid for 3 years.
Prior Certification
- None specified
Exam Format
The Data Engineering on Microsoft Azure exam is a Multiple-choice
Passing Conditions
To pass Data Engineering on Microsoft Azure exam, applicants must achieve a minimum score of Pass at least 700 points (out of 1000)
Who Should Take
This exam is for IT professionals who design and implement solutions for data engineering on Azure.
- Azure Data Engineer
- Data Scientist
- Business Intelligence Developer
Prerequisites
1-2 years of experience in designing and implementing data engineering solutions
Or can substitute with certifications:
- Certified Analytics Developer (CAD) certification
- Microsoft Certified: Azure Developer Associate certification
- Microsoft Certified: Data Platform Developer Associate certification
Certification Process
- Register for the exam
- Prepare for the exam by studying Microsoft Azure resources and taking practice tests
- Take the exam at a testing center
- Receive your certification after passing the exam
Domains with Weights
- Design and Implement a Data Platform (25%): Design and implement a scalable, secure, and performant data platform using Azure services.
- Ingest and Process Data (20%): Ingest and process data from various sources using Azure services such as Azure Data Factory, Azure Functions, and Azure Databricks.
- Create and Manage Data Warehouses and Lakes (20%): Create and manage data warehouses and lakes using Azure services such as Azure Synapse Analytics and Azure Data Lake Storage.
- Develop and Deploy Data Solutions (30%): Develop and deploy data solutions using Azure services such as Azure Machine Learning, Azure Functions, and Azure Databricks.
- Monitor and Optimize Data Workloads (5%): Monitor and optimize data workloads using Azure services such as Azure Monitor, Azure Log Analytics, and Azure Advisor.
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