Microsoft Certified: Azure Data Engineer Associate Certification Exam Practice Test Questions, Microsoft Certified: Azure Data Engineer Associate Exam Dumps

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The Microsoft Certified: Azure Data Engineer Associate certification validates the expertise of the candidates in integrating, consolidating, and transforming data from different unstructured and structured data systems into specific structures that are appropriate for analytics solutions building. The applicants for this certificate should possess the relevant skills in designing, monitoring, optimizing, and implementing data platforms for fulfilling data pipeline needs.

To obtain this associate-level certification, the individuals must pass the qualifying exam, which is Microsoft DP-203: Data Engineering on Microsoft Azure. The target candidates for this certificate are Azure Data Engineers. They are the professionals with the job role dedicated to helping the stakeholders gain insights into data. They do this by exploring, maintaining, and building a compliant and secure data processing pipeline through the use of various techniques and tools. These specialists utilize different Azure data languages and services to produce and store enhanced and cleansed datasets for analysis. The Azure Data Engineers also assist in ensuring that data stores and data pipelines are efficient, high-performing, reliable, and organized with specific sets of business constraints and requirements.

The certification does not have any official prerequisites. However, the candidates must have an extensive understanding of data processing languages. These include Python, Scala, or SQL. They also need to have a grasp of data architecture patterns and parallel processing.

Exam Details

The Microsoft DP-203 certification exam is a 120-minute test covering a range of topics. The exam can only be taken in English and registration is done through Pearson VUE. The test evaluates the knowledge and skills of the learners in designing and implementing data storage, designing and implementing data security, monitoring and optimizing data processing & data storage, as well as designing and developing data processing.

The fee for taking this exam is $165 and this applies to one delivery of the test. The candidates who do not attain the passing score during their first sitting will be required to pay another fee and retake the exam to obtain their certification. The applicants must wait for 24 hours after the first attempt to sit for the test again. After the second try, they must wait for 14 days to retake the exam.

There are different preparation options that the learners can explore to prepare for their certification exam. Microsoft offers six self-paced learning paths for the DP-203 test. These cover different modules and can be accessed on the official website. Currently, this exam does not have any related instructor-led training course but the candidates can take advantage of the tools on other reputable platforms to enforce their knowledge and skills in the domain of the test. It is crucial to invest some time into taking mock exams to develop your time management skills and get familiar with the pattern of the test.

Exam Topics

The Microsoft DP-203 certification exam measures the skills of the candidates in a range of topics. The applicants must develop competence in these domains before attempting the test. The highlights of the areas covered in this exam are enumerated below:

Data Storage Design & Implementation: 40-45%

• Data Storage Structure Design: It covers the skills in designing for data pruning and efficient querying, designing a distribution strategy and a data archiving solution; recommending file types for storage and analytical queries; designing folder structures that represent data transformation levels.
• Partition Strategy Design: The candidates should develop competence in designing partition strategies for files, analytical workloads, performance/efficiency, and Azure Synapse Analytics. It also covers their skills in identifying when partitioning is required within Azure Data Lake Storage Gen2.
• Serving Layer Design: The examinees need the skills in designing star schemas, dimensional hierarchy, analytical stores, incremental loading slowly changing dimensions, and metastores within Azure Databricks and Azure Synapse Analytics.
• Physical Data Storage Structures Implementation: It requires that the applicants have the relevant skills in implementing compression, partitioning, data redundancy, sharding, data archiving distribution, and various table geometries with the Azure Synapse Analytics pools.
• Logical Data Structures Implementation: It covers one’s skills in building the temporal data solution logical folder structure, external tables, and slowly changing dimension as well as implementing folder and file structures for data pruning and efficient querying.
• Serving Layer Implementation: It requires your competence in maintaining metadata, delivering data within relational star schemas and data within Parquet files, and implementing dimensional hierarchies.

Data Processing Design & Development: 25-30%

• Data Transformation and Ingestion: The candidates should have the expertise in transforming data with the use of Apache Spark, Transact-SQL, Data Factory, Stream Analytics, Scala, and Azure Synapse Pipelines. This topic also requires their skills in cleansing data, splitting data, encoding & decoding data, shredding JSON, configuring error handling for transformations, as well as normalizing & denormalizing values.
• Batch Processing Solution Development & Design: It covers the skills in developing batch processing solutions with the use of Data Lake Data Factory, Spark, Azure Databrics, and Synapse Pipelines. It also covers one’s competence in scaling resources, configuring batch sizes, handling late-arriving data, missing data, and duplicate data, upserting data, regressing to previous states, and configuring batch retentions, among others.
• Stream Processing Solution Development & Design: It requires the skills in handling schema drift, processing time-series data, across partitions, and within one partition. It also covers scale resources, upserting data, handling interruptions, designing & creating tests for data pipelines, designing & configuring exception handling, and designing stream processing solutions, among others.
• Pipeline and Batch Management: The individuals should demonstrate their competence in triggering batches, validating batch loads, handling failed batch loads, managing Spark jobs within pipelines, scheduling and managing data pipelines within Data Factory/ Synapse Pipelines.

Data Security Design and Implementation: 10-15%

• Design of Security for Data Standards and Policies: It requires the students’ skills in designing a data auditing strategy, data masking strategy, data privacy, data retention policy, and data encryption for data in transit and data at rest.
• Data Security Implementation: It covers your competence in implementing data masking, Azure RBAC, column-level and row-level security, data retention policy, data auditing strategy, resource tokens within Azure Databricks, and managing sensitive information.

Data Processing & Data Storage Monitoring and Optimization: 10-15%

• Data Processing & Data Storage Monitoring: It requires the candidates’ competence in implementing logging utilized by Azure Monitor; configuring monitoring services; monitoring data pipeline performance, cluster performance, and monitoring & updating statistics about data over systems.
• Data Processing & Data Storage Troubleshooting and Optimization: The test takers should demonstrate their competence in compacting small files, optimizing resource management, handling skew-in data, tuning shuffle within a pipeline, troubleshooting failed spark job and failed pipeline run. It also requires their skills in handling data spills, tuning queries with cache and indexer.

Career Path

Earning a certification from a renowned vendor boosts a professional’s potential in the IT world. With many job opportunities, a certificate can surely set you apart from the crowd. With the Microsoft Certified: Azure Data Engineer Associate certification, the successful candidates can explore numerous job roles. Some of them include an Associate Data Engineer, a Data Engineer, an Application Support Engineer, a Machine Learning Engineer, and an Automation Engineer, among others. The average annual salary for these titles is around $92,777.

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