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Exam DP-203: Data Engineering on Microsoft Azure –
Skills Measured
Audience Profile
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.
Candidates for this exam should have subject matter expertise working with people, processes, and technologies to continuously deliver business value.
Responsibilities for this role include designing and implementing strategies for collaboration, code, infrastructure, source control, security, compliance, continuous integration, testing, delivery, monitoring, and feedback.
A candidate for this exam must be familiar with both Azure administration and development and must be expert in at least one of these areas.
NOTE: The bullets that appear below each of the skills measured are intended to illustrate how we are assessing that skill. This list is NOT definitive or exhaustive.
NOTE: Most questions cover features that are General Availability (GA). The exam may contain questions on Preview features if those features are commonly used.
Develop an Instrumentation Strategy (5-10%)
Manage source control (10-15%)
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