Introduction to Newly Announced Microsoft DP-203 Exam
With the diverse certifications of Microsoft, it satisfies the needs and expertise of all the fields of IT. If you are a data engineer and looking for a perfect certification to boost your understanding, skills, and representation on your resume, then Azure Data Engineering Associate certification is there for you. A candidate who is applying for this certification should have an in-depth understanding of the corresponding data processing languages including SQL, Python, or Scala. It requires you to have the basics of data processing and data architecture patterns.
If you are applying for a DP-203 exam to secure Azure Data Engineering Associate certification for you then you must prepare well for the exam to prepare the opportunity. Dumpsgate brings you prep material in the form of DA-203 exam dumps 2022. These exam dumps will assist you in your preparation with the help of authentic and updated exam dumps. Let’s explore more about the exam in the rest of the article.
Who is the Target audience of the Microsoft DP-203 Exam?
The target audience of the exam DP-2033 includes those who have the expertise in the integration, transformation, and consolidation of data. This processing of data is dome from different data structures which can be structured and unstructured to a structure that is optimum for analytic solutions.
The responsibility of the data engineer involves helping the stakeholder to understand the data and corresponding situation by building secure and compliant pipelines for data processing with the help of various tools and d techniques. In the process, various Azure services and data languages are used to store and clean data so that enhanced data sets are produced. The v efficiency, proper management and reliability of data pipelines is also guaranteed by the data engineers. Furthermore, they are also responsible for designing, monitoring, implementing and optimizing data platforms to make the fit for corresponding data pipelines.
What are the skills measured in Latest Microsoft DP-203 Exam?
Following are the skills measured in the form of syllabus content is DP-203.
Design and Implement Data Storage – (40%-45%)
This part is divided into six subdomains as follows
Designing a data storage structure
It includes the following syllabus contents
- Designing of an Azure Data Lake solution
- Recommendation of the file types for storage
- Recommendation of file types for analytical queries
- Designing for the efficient querying
- Designing for the data pruning
- Designing a folder structure that can represent the extent and level of data transformed.
- Designing of a distribution strategy
- Designing of a data archiving solution
Designing a partitioning strategy
- Designing a partitioning strategy for the files
- Designing a partitioning strategy for analytical workloads
- Designing of a partitioning strategy for efficiency/performance
- Designing a partitioning strategy for Azure Synapse Analytics
- Identification of scenarios when partitioning is required for the Azure Data Lake Storage Gen2
Designing the serving layer
- Designing of star schemas
- Designing slowly changing dimensions
- Designing a dimensional hierarchy
- Designing a solution for temporal data
- Designing for incremental loading
- Designing analytical stores
- Designing metastores in Azure Synapse Analytics and Azure Databricks
Implementation of physical data storage structures
- Implementation of compression
- Implementation of partitioning
- Implementation of sharding
- Implementation of different table geometries with Azure Synapse Analytics pools
- Implementation of data redundancy
- Implementation of distributions
- Implementation of data archiving
Implementation of logical data structures
- Building of a temporal data solution
- Building of a slowly changing dimension
- Building of a logical folder structure
- Building of external tables
- Implementation of file and folder structures for efficient querying and data pruning
Implementation of the serving layer
- Delivering the data in a relational star schema
- Delivering the data in Parquet files
- Maintaining the metadata
- Implementation of a dimensional hierarchy
Design and Develop Data Processing – (25%-30%)
This part is divided into four subdomains which are stated below.
Ingest and transform data
- Transformation of data with the help of Apache Spark
- Transformation of data with the help of Transact-SQL
- Transformation of data with the help of Data Factory
- Transformation of data with the help of Azure Synapse Pipelines
- Transformation of data with the help of Stream Analytics
- Cleaning of data
- Splitting the data
- Shredding JSON
- Encoding and decoding data
- Configuring error and handling for the transformation
- Normalizing and de-normalizing values
- Transformation of data by using Scala
- Performing data exploratory analysis
Design and develop a batch processing solution
- Developing batch processing solutions by using Data Factory, Data Lake, Spark, Azure Synapse Pipelines, PolyBase, and Azure Databricks
- Creation of the data pipelines
- Designing and implementing the incremental data loads
- Designing and developing slowly changing dimensions
- Handling of the security and compliance requirements
- Scaling the resources
- Configuration of the batch size
- Designing and creating the tests for data pipelines
- Integration of Jupyter/Python notebooks with corresponding data pipeline
- Handling the duplicate data, missing data and late-arriving data
- Upserting data
- Regressing to a previous state
- Designing and configuring exception handling
- Configuration of batch retention
- Designing a batch processing solution
- Debugging the Spark jobs with the help of Spark UI
Design and develop a steam processing solution
- Developing a stream processing solution with the help of Stream Analytics, Azure Databricks, and Azure Event Hubs
- Processing data with the help of Spark structured streaming
- Monitoring for performance and functional regressions
- Designing and creating the windowed aggregates
- Handling the schema drift
- Processing time-series data
- Processing across partitions
- Processing within one partition
- Configuration of checkpoints/watermarking during processing
- Scaling the resources
- Designing and creating tests for data pipelines
- Optimization of pipelines for analytical or transactional purposes
- Handling the interruptions
- Designing and configuring the exception handling
- Upserting the data
- Replaying the archived stream data
- Designing a stream processing solution
Manage batches and pipelines
- Triggering the batches
- Handling the failed batch loads
- Validating the batch loads
- Management of data pipelines in Data Factory/Synapse Pipelines
- Scheduling data pipelines in Data Factory/Synapse Pipelines
- Implementation of version control for pipeline artifacts.
- Management of Spark jobs in a pipeline
Design and Implement Data Security – (10%-15%)
This domain is divided into two sub-domains.
Designing security for data policies and standards
- Designing the data encryption for data at rest and data in transit
- Designing a data auditing strategy
- Designing a data masking strategy
- Designing for data privacy
- Designing a data retention policy
- Designing to purge data based on business requirements
- Designing the Azure role-based access control (Azure RBAC) and POSIX-like Access Control List (ACL) for Data Lake Storage Gen2
- Designing the row-level and column-level security
Implementing data security
- Implementation of data masking
- Encryption of data at rest and data in motion
- Implementation of row-level and column-level security
- Implementation of Azure RBAC
- Implementation of POSIX-like ACLs for Data Lake Storage Gen2
- Implementation of data retention policy
- Implementation of data auditing strategy
- Management of identities, keys, and secrets for various data platform technologies
- Implementation of secure endpoints both private and public
- Implementation of resource tokens in Azure Databricks
- loading DataFrame with sensitive information
- Writing encrypted data to tables or Parquet files
- Management of sensitive information
Monitor and Optimize Data Storage and Data Processing – (10%-15%)
This part is divided into further two parts as follows.
Monitoring data storage and data processing
- Implementation of logging used by Azure Monitor
- Configuring the monitoring services
- Measurement of the performance of data movement
- Monitoring and updating statistics about data across a system
- Monitoring the performance of the data pipeline
- Measurement of query performance
- Monitoring the cluster performance
- Understanding the custom logging options
- Scheduling and monitoring pipeline tests
- Interpretation of Azure Monitor metrics and logs
- Interpretation of a Spark directed acyclic graph (DAG)
Optimizing and troubleshooting data storage and processing
- Compact small files
- Rewriting user-defined functions (UDFs)
- Handling skew in data
- Handling data spill
- Tuning the shuffle partitions
- Finding the shuffling in a pipeline
- Optimization of resource management
- Tuning the queries by using indexers
- Tuning the queries by using cache
- Optimizing pipelines for analytical or transactional purposes
- Optimizing pipeline for descriptive versus analytical workloads
- Troubleshooting a failed spark job
- Troubleshooting a failed pipeline run
What is the exam pattern of the latest Microsoft DP-203?
The exam pattern followed by DP-203 is as follows.
- The exam code is DP-203.
- The exam duration is 150 minutes.
- The number of questions is 40 – 60 questions.
- The question type is MCQs (Multiple Choice Questions)
- The required Passing score is 700 out of 1000.
- The exam fee is $165 USD.
- Exam languages are English, Chinese (Simplified), Japanese, Korean, German, French, Spanish, Portuguese (Brazil), Arabic (Saudi Arabia), Russian, Chinese (Traditional), Italian, Indonesian (Indonesia).
- Schedule Exam Here
- Download the Latest Real Exam questions for DP-203.
- Learn more about Microsoft Retake Policy here
How to prepare for DP-203?
if you are a data engineer and trying to boost the effectiveness of your skills by taking the DP-203 exam then cheers to your decision. Now to nail the exam, you must require a source in the form of a guide to prepare for the exam. Dumpsgate provides you with a compiled source in the form of updated DP-203 exam dumps. These PDF dumps are prepared by the experts and hence include all the relevant requirements.
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Frequently Asked Questions for DP-203 Exam
What is DP-203 certification?
DP -203 certification is known as Azure Data Engineering Associate. Like every certification, it also has exam that is required to be cleared to avail of the certification and that exam is known as the DP-203 exam.
Is DP-203 difficult?
DP-203 with its length syllabus content is difficult but not impossible to pass. To help you go through with this difficulty of preparation, Dumpsgate offers you DP-203 exam dumps prepared by experts. These exam dumps will make sure that you prepare your exam covering the whole syllabus guarantying a passing score.
Can I Pass DP-203 With Dumps?
With the right exam dumps proper devotion and effort, you can ass the DP-203 exam on the go. Dumpgate brings you real and authentic exam dumps covering all the exam questions for you. these PDF dumps are compiled source and hence help you cover your syllabus effectively in a short time period.
How long does it take to prepare for DP-203?
With Dumpsgate exam dumps and real hard work, even a month is more than sufficient for the preparation of DP-203.
Does DP-203 expire?
DP-203 is valid for one year and after that candidate has to retake the exam for renewal.
Who should take DP-203?
The exam is a perfect ladder towards a successful career for data engineers. It will not only polish your knowledge and skills rather will represent your skills in front of the employer too.
How many questions are there in the DP-203 exam?
Where can I get DP-203 Dumps?
If you are searching for DP-203 exam dumps, then you are in the right place because Dumpsgate offers you authentic and updated exam dumps prepared by experts.
Is DP-203 Dumps Really Helpful?
Dumpsgate DP-203 exam dumps are prepared by the experts and contain the exam question covering all the syllabus in a compiled form. Preparing from these exam dumps will help you to cover all the syllabus in no time.
DP-203 Passing Score?
Require passing score for DP-203 is 700 out of 1000.
What is DP-203 Exam Retake Policy?
If a candidate fails a DP-203 exam on the first attempt, he or she must wait at least a 24-hour period before retaking it. If the candidate does not obtain a passing grade on the second take, he or she should re-gain their expertise and wait at least 14 days.
What are the Prerequisites for DP-203 Exam?
You should have Basic experience of using Microsoft Azure for DP-203 Exam Certification.
Below are some useful links for other Azure Certifications
- Microsoft Certified: Azure – Fundamentals Exam AZ-900
- Microsoft Certified: Azure AI – Fundamentals Exam AI-900
- Microsoft Certified: Azure Data – Fundamentals Exam DP-900
- Microsoft Certified: Azure Administrator – Associate Exam AZ-104
- Microsoft Certified: Azure Developer – Associate Exam AZ-204
- Microsoft Certified: Azure Security Engineer – Associate Exam AZ-500
- Microsoft Certified: Azure AI Engineer Associate Exam AI-102
- Microsoft Certified: Azure Data Scientist – Associate Exam DP-100
- Microsoft Certified: Azure Data Engineer – Associate Exams DP-203
- Microsoft Certified: Azure Database Administrator – Associate Exam DP-300
- Microsoft Certified: Azure Solutions Architect Expert Exams AZ-305
- Microsoft Certified: Azure DevOps Engineer – Expert Exam AZ-400