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About DP-203 Exam
The Microsoft DP-203: Data Engineering on Microsoft Azure test evaluates candidates’ data engineering skills. Competencies measured by this certification exam include the ability to integrate, transform, and consolidate data from different structured as well as unstructured data systems to a form that suits the development of analytics solutions. Those who succeed in passing the Microsoft DP-203 exam are awarded the Microsoft Certified: Azure Data Engineer Associate accreditation.
Who Should Apply For The Evaluation?
The target audience for the DP-203 evaluation is individuals who aspire to establish a career as Azure Data Engineers. To become the right candidate for the test, these persons need to possess strong knowledge covering languages for data processing such as SQL, Scala, or Python. Also, a good understanding of parallel processing as well as data infrastructure patterns are essential for successful completion of the DP-203 exam.
Exam DP-203 consists of approximately 40 to 60 questions that are to be completed by test-takers within 100 minutes. Candidates can sit for the test in four available languages, including English, Korean, Japanese, and Simplified Chinese. The associated certification is awarded provided the required passing score is achieved, starting from 700 points with the maximum 1000 points. To register for the evaluation, applicants have to pay a registration fee of $165. The exam cost can vary depending on the country where it is proctored. So, before taking the real exam, check the actual price for your location, by browsing the official test webpage.
Candidates for the DP-203 evaluation are assessed based on their knowledge of four major domains. These are described in detail below:
- Creating and executing data storage
The first topic of the DP-203 test is divided into six subsections. It starts with creating the structure for data storage. What is covered includes creating a solution for Azure Data Lake, recommending file types for storage, and developing for effective querying. The next area concerns developing a strategy for partition. This includes the ability to develop star schemas, slowly transforming dimensions, dimensional ranking, solution targeting temporal data, analytical stores, and more. Implementation of structures related to physical data storage is what comes next. It covers the execution of compression, partitioning, sharding, data redundancy, and more. Another subsection covers the execution of structures for logical data. This includes proficiency in building a temporal solution for data, slowly transposing dimension, external tables, and more. The last matter entails the capacity to execute the serving layer. Competencies covered here involve delivering data in ways including relational star schema and Parquet files. The remaining subsections are focused on maintaining metadata and executing a dimensional layer.
- Creating and developing data processing
Within the successive skill area of the DP-203 evaluation, candidates need to demonstrate their understanding of four topics. The first one concerns ingesting and transforming data. Some things to note here include transforming data with the use of Apache Spark, Transact SQL, Data Factory, and Stream Analytics, among others. Besides, test-takers must be capable of cleansing data, splitting data, encoding and decoding data, and more. Moving on, examinees should show their proficiency in creating and developing a solution for batch processing. This covers developing these solutions using Data Lake, Data Factory, Azure Synapse Pipelines, Azure Databricks, and others. It also covers creating data pipelines, scaling resources, handling missing data, creating and configuring exception handling, and more. Creating and developing a solution for stream processing is another matter addressed under this topic. This goes into developing the solution using Azure Databricks, Stream Analytics, and others. In addition, processing data with the use of structured streaming linked to Spark, handling schema drift, processing across partitions is covered. The topic devoted to managing batches as well as pipelines is what brings this topic to a close. Within it, test-takers should have a comprehension of triggering batches, handling batched loads that have failed, and validating batch loads, among other things.
- Creating and executing data security
The section that follows the above skill area of the DP-203 test captures the development of security aimed at data policies and standards. This covers creating data encryption targeting data which is at rest as well as in transit, creating a strategy for auditing data, designing for data privacy, and other competencies. Next comes the execution of data security. This encompasses executing data masking, encrypting data which is at rest and that is in motion, executing Azure RBAC, executing a retention policy for data, and executing an auditing strategy for data. Other skills included are managing identities, secrets, and keys across varying technologies for data platform, executing secure endpoints (both private and public), and managing sensitive information, among others.
- Monitoring and optimizing data storage & data processing
The final topic inspects issues concerning monitoring data storage as well as data processing. It includes executing logging that Azure Monitor uses and configuring monitoring services. Other skills evaluated here include measuring how data movement performs in addition to monitoring and updating statistics about data within the system. Besides, candidates need to dwell on measuring query performance, monitoring cluster performance, comprehending options for custom logging, as well as scheduling and monitoring pipeline tests. Within this topic, test-takers should also demonstrate about optimizing and troubleshooting data storage & data processing. This covers compacting small files, handling skew within data, tuning shuffle partitions, optimizing resource management, and other competencies.
The DP-203 exam and the related certificate offer an exceptional opportunity for those intending to build their careers in the data engineering domain. The work in the role of an Azure Data Engineer comprises helping stakeholders comprehend the data via exploration. Other responsibilities include building and maintaining security as well as compliant pipelines for data processing through the use of varying tools and techniques.
Azure Data Engineers utilize various Azure-based data services as well as languages for storing and producing cleansed and enhanced analysis datasets. Besides, these professionals are responsible for making sure that all data pipelines and data stores perform highly and are efficient, organized, and reliable in accordance with given business demands and constraints. They are also required to deal with unanticipated challenges while minimizing data loss.
Azure Data Engineers are in high demand in the job market, which entails generous remunerations. As estimated by ZipRecruiter.com, their earnings come to around $139k yearly. The maximum pay for these professionals can reach $181k per annum.