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Why do you need to get Microsoft DP-203 Exam
Are you ready to take the Data Engineering on Microsoft Azure Exam
DP-203 Exam: Key Points and Focus Areas
The Microsoft Data Platform, or MDP, is a collection of products and services that primarily target companies whose business involves large volumes of data. These companies are often referred to as data-driven businesses. The MDP helps such businesses store, process, and analyze the massive amounts of data that their operations produce. The Microsoft Data Platform Certification (Microsoft DP-203) exam tests a candidate's knowledge of the Microsoft technologies that are used to build a cloud computing infrastructure for Big Data analytics. Free demo material that helps with the preparation for the DP-203 exam includes sample questions and answers, practice exams, and a training guide. Microsoft DP-203 Dumps provide all the test-taking tools necessary for passing the DP-203 exam, including a test engine and a simulation mode. If you are reading this article it means you are interested in pursuing a Microsoft certification path or already have one. Great! You've taken an important first step to become a Data Engineer on Microsoft Azure certification.
All the details of Microsoft DP-203 Exam format?
Language: English
Exam Length: 40-60 question
Exam Format: multiple-choice
Exam Duration: 130 minutes
Passing score: 75%
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-203
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Skills measured
- Design and implement data storage (40-45%)
- Monitor and optimize data storage and data processing (10-15%)
- Design and implement data security (10-15%)
- Design and develop data processing (25-30%)
Microsoft DP-203 Deutsch Exam Syllabus Topics:
| Section | Weight | Objectives |
| Monitor and optimize data solutions | 30-35% | - Monitor data processing
- 1. Monitor pipelines using Azure Monitor
- 2. Troubleshoot data workflows
- Optimize performance
- 1. Optimize query performance in Synapse
- 2. Optimize data storage performance
|
| Design and implement data storage | 25-30% | - Develop data storage solutions
- 1. Implement relational data stores (Azure SQL, Synapse)
- 2. Implement Azure Blob Storage solutions
- 3. Implement Azure Data Lake Storage solutions
- Design data storage structures
- 1. Recommend appropriate storage accounts and services
- 2. Design a data serialization format strategy
- 3. Design a data partitioning strategy
|
| Develop data processing | 40-45% | - Ingest and transform data
- 1. Implement stream processing solutions
- 2. Use Azure Data Factory for pipelines
- 3. Implement batch processing solutions
- Develop data transformation logic
- 1. Use Spark in Azure Databricks
- 2. Use SQL-based transformations
|
| Secure data solutions | | - Implement data security
- 1. Manage access control with Azure RBAC
- 2. Implement encryption at rest and in transit
- Ensure compliance
- 1. Use Microsoft Purview for governance
|