Microsoft Certified: Azure Data Engineer Associate

certifications
2022-11-26
2 minutes to read

Passed

Today I took and passed DP-203 obtaining the Azure Data Engineer Associate accreditation.

Renewed

Update 2023-11-26: I have recently renewed this certification, extending my accreditation until 2024-11-26.

Exam DP-203

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.

Skills measured

Design and implement data storage (40—45%)
Design and develop data processing (25—30%)
Design and implement data security (10—15%)
Monitor and optimize data storage and data processing (10—15%)

Earning the Azure Data Engineer Associate certification validates the skills and expertise in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions. Candidates have a solid knowledge of data processing languages, such as SQL, Python, or Scala, and they need to understand parallel processing and data architecture patterns.