To convert unstructured data into structured data, organizations hire certified Azure Data Engineers. Furthermore, obtaining relevant and appropriate data will help businesses make better decisions and give them a better outlook for the future. The proper use of information can also improve customer service. This is one reason for the sudden increase in demand for data engineers and data science. This blog will provide a step-by–step guide on how to become a Microsoft Certified Azure Data Engineer. We also provide a comprehensive preparation guide for Azure Exam DP203: Data Engineering on Microsoft Azure, along with the training and supervision.
The certification of an Azure Data Engineer validates your ability to combine, transform and combine data from multiple systems into structures suitable for building analytics solutions.
Azure Data Engineer Roles & Responsibilities
The Azure Data Engineer certification requires that applicants have the ability to combine, transform, and combine data from various structured and unstructured data sets into solutions that can be used for analytics.
This role has the responsibility of helping stakeholders understand data by exploring, building and maintaining secure data processing pipelines using various tools and methods. The expert uses many Azure data services and linguistics in order to store and provide improved datasets for analysis.
An Azure Data Engineer supports the assurance that data pipelines or data repositories perform well, are productive, organized, secure, and have a specific set of business requirements and restraints. This professional is able to quickly resolve unanticipated issues and minimize data loss. An Azure Data Engineer also plans, implements, monitors, and optimizes data principles in order to address data pipeline deficiencies.
Knowledge is required
Candidats for this credential need to have a solid knowledge of data processing linguistics such as Python, SQL or Scala. They also need to understand parallel processing and data architecture models.
Let’s get to the course outline.
DP-203 Exam Structure
Microsoft has provided a course outline for exam DP-203. It includes the most important sections to help you gain more real knowledge during your training time. These topics are:
Design and implement data storage
Designing a data storage system
Designing an Azure Data Lake solution (Microsoft documentation:Azure Data Lake Storage Gen2)
Suggesting the file types for storage (Microsoft Documentation:Example scenarios)
Recommend file types for analytical queries (Microsoft Docation:Query data in Azure Data Lake with Azure Data Explorer).
Efficient querying (Microsoft Documentation:Designing for querying)
Folder structure that shows the levels of data transformation (Microsoft Documentation:Copying and transforming the data in Azure Data Lake Storage Gen2)
Designing a distribution plan (Microsoft Documentation:Designing distributed tables)
Data Archiving Solution
Designing a partition strategy
Partition plan for the files
A partition plan to support analytical workloads
Partition strategy for efficiency/performance (Microsoft Documentation:Designing the partitions for query performance)
Making a partition strategy for the Azure Synapse Analytics (Microsoft Documentation:Partitioning tables)
How to identify when partitioning is necessary in the Azure Data Lake Storage Gen2
Designing the serving layer
Star schemas (Microsoft Documentation:Overview of Star schema)
Making slowly changing dimensions
Making a dimensional hierarchy (Microsoft Documentation:Hierarchies in tabular models)
Solution for temporal data (Microsoft Documentation:Temporal tables in the Azure SQL Database and Azure SQL Managed Instance)
Incremental loading (Microsoft DB)