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What should I know before taking the Microsoft DP-203 exam?
Microsoft offers Data Engineering on Microsoft Azure certification to those who wish to demonstrate their knowledge of data engineering on the Microsoft Cloud. The exam comprises multiple-choice questions, and each question is worth one mark. The candidates are required to attempt 60 questions in total, i.e., within 130 minutes. In order to take this exam, the candidates are required to have knowledge of the fundamental concepts related to the subject matter. Knowledge of basic cloud computing concepts (such as virtual machines, virtual networks, etc.) would be beneficial for the candidates. Microsoft DP-203 exam dumps contains an online study guide that explains all the concepts and answers to practice questions. Candidates should try to understand the concepts completely to gain good marks on the test.
What is Microsoft DP-203 Certification
Microsoft DP-203 (Designing Data Platform Solutions on Microsoft Azure) certification is a great way to validate your hands-on experience with cloud platforms, data architecture, and database technologies. This exam is designed to determine the competency of candidates to design distributed data solutions for enterprise applications based on Azure technologies. Before you begin studying for this exam, there are a few terms that you should familiarize yourself with. First and foremost, you should understand the difference between Microsoft SQL Server, Microsoft SQL Database, and Microsoft Azure SQL Database. Exam objectives are associated with these products; therefore, it is important to know when you will be tested on each one. Microsoft DP-203 Dumps tests a candidate's knowledge of Microsoft technologies used for building a data platform and cloud environment. Microsoft DP-203 is a certification of data engineers. The certification exam is designed to test the skills of designing, deploying, and managing Microsoft HDInsight and Microsoft Azure SQL Data Warehouse clusters for business intelligence and analytics solutions.
Data Engineering on Microsoft Azure Exam Certification Details:
| Books / Training | DP-203T00: Data Engineering on Microsoft Azure |
| Exam Code | DP-203 |
| Sample Questions | Data Engineering on Microsoft Azure Sample Questions |
| Passing Score | 700 / 1000 |
| Duration | 150 mins |
| Number of Questions | 40-60 |
| Schedule Exam | Pearson VUE |
| Exam Name | Microsoft Certified - Azure Data Engineer Associate |
| Exam Price | $165 (USD) |
Exam DP-203: Data Engineering on Microsoft Azure
Candidates for this exam should have subject matter expertise integrating, transforming, and consolidating data from various structured and unstructured data systems into a structure that is suitable for building analytics solutions.
Azure Data Engineers help stakeholders understand the data through exploration, and they build and maintain secure and compliant data processing pipelines by using different tools and techniques. These professionals use various Azure data services and languages to store and produce cleansed and enhanced datasets for analysis.
Azure Data Engineers also help ensure that data pipelines and data stores are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints. They deal with unanticipated issues swiftly, and they minimize data loss. They also design, implement, monitor, and optimize data platforms to meet the data pipelines needs.
A candidate for this exam must have strong knowledge of data processing languages such as SQL, Python, or Scala, and they need to understand parallel processing and data architecture patterns.
Part of the requirements for: Microsoft Certified: Azure Data Engineer Associate
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-203
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Microsoft DP-203 Deutsch Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design and develop data processing | 25–30% | - Design data processing pipelines
|
| Topic 2: Design and implement data security | 10–15% | - Protect data at rest and in transit
|
| Topic 3: Design and implement data storage | 40–45% | - Design data storage structures
|
| Topic 4: Monitor and optimize data storage and data processing | 10–15% | - Optimize performance and cost
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