DP-203: Data Engineering on Microsoft Azure-Course Overview

Note: Exam DP-203 is replacing exams DP-200 and DP-201. DP-200 and DP-201 will retire on June 30, 2021.

The DP-203 Data Engineering on Microsoft Azure certification training course from CloudThat offers candidates proper training and relevant study material to prepare and successfully clear the DP-203 exam.

After Completing DP-203 certification training, students will be able to:

  • Design and implement data storage
  • Design and develop data processing
  • Secure, monitor, and optimize data storage
  • Secure, monitor, and optimize data processing

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Key Features of DP-203 certification training

  • Our training modules have 50% - 60% hands-on lab sessions to encourage Thinking-Based Learning (TBL)
  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL)
  • Microsoft certified instructor-led training and mentoring sessions to develop Competency-Based Learning (CBL)
  • Well-structured use-cases to simulate challenges encountered in a Real-World environment
  • Integrated teaching assistance and support through experts designed Learning Management System (LMS) and ExamReady platform with Study Guide
  • Being a Microsoft Learning Partner provides us with the edge over competition

Who Should Attend:

  • Subject matter expertise in integrating, transforming, and consolidating data from various structured, unstructured, and streaming data systems into a suitable schema for building analytics solutions and data processing.

What are the prerequisites for DP-203 certification training?

The prerequisites of DP-203 exam include:

  • A foundational knowledge of core data concepts and how they’re implemented using Azure data services.
  • Experience in designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value using Microsoft Power BI.

Learning Objectives of DP-203 Data Engineering on Microsoft Azure Training

  • Get started with data engineering on Azure: It provides a comprehensive platform for data engineering including introduction to services like ADLS Gen 2, Azure Synapse Analytics.
  • Build data analytics solutions using Azure Synapse serverless SQL pools: Learn how to store data in, transform data using, secure and manage the serverless SQL pools.
  • Perform data engineering with Azure Synapse Apache Spark Pools: This module covers how to store data in, analyze data using, and use delta lake of Apache Spark Pools.
  • Work with Data Warehouses using Azure Synapse Analytics: Understanding on how to load, analyze, optimize, and manage data in relational data warehouse.
  • Transfer and transform data with Azure Synapse Analytics pipelines: Azure Synapse Analytics enables data integration through the use of pipelines, which you can use to automate and orchestrate data transfer and transformation activities.
  • Work with Hybrid Transactional and Analytical Processing Solutions using Azure Synapse Analytics: Learn how to integrate Synapse Analytics with other Azure Data Services. Hybrid Transactional and Analytical Processing (HTAP) is a technique for near real time analytics without a complex ETL solution. In Azure Synapse Analytics, HTAP is supported through Azure Synapse Link.
  • Implement a Data Streaming Solution with Azure Stream Analytics: Discover techniques for ingesting, processing, and visualizing real-time data with Data streaming solutions.
  • Govern data across an enterprise: Learn how to use Microsoft Purview to register and scan data, catalog data artifacts, find data for reporting, and manage Power BI artifacts to improve data governance in your organization.
  • Data engineering with Azure Databricks: Learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run large data engineering workloads in the cloud. The learning objectives are designed to impart a comprehensive understanding of Azure Data Platform as a tool for data analysis and visualization. They aim to prepare participants for both the DP-203 exam and real-world data engineering scenarios.

What makes CloudThat a compelling choice for DP-203 training for Data Engineering on Microsoft Azure?

  • With over 11 years of experience in training and consulting, we at CloudThat bring extensive expertise to our DP-203 training for Data Engineering on Microsoft Azure.
  • CloudThat has successfully trained a vast number of professionals, approximately 6.5 lakh individuals, and provided training services to more than 100 corporate clients across the globe.
  • Our Microsoft certified trainers (MCTs) for DP-203 Data Engineering on Microsoft Azure course emphasize a significant portion of hands-on lab sessions, ranging from 50% to 60%, to foster a learning approach centered around scenario-based problem-solving.
  • Our DP 203-certified trainer facilitates instructor-led training and mentoring sessions that focus on developing competency-based learning (CBL) methodologies. These sessions are designed to enhance participants' skills and knowledge through practical application and real-world scenarios.
  • CloudThat offers training and consulting services with a proven track record of successfully delivering numerous projects, including engagements with Fortune 500 companies.
  • CloudThat has established itself as a Microsoft Partner, as well as partnering with other renowned industry leaders such as AWS, GCP, and VMWare

Course Outline Download Course Outline

Implement a partition strategy

  • Implement a partition strategy for files
  • Implement a partition strategy for analytical workloads
  • Implement a partition strategy for streaming workloads
  • Implement a partition strategy for Azure Synapse Analytics
  • Identify when partitioning is needed in Azure Data Lake Storage Gen2

Design and implement the data exploration layer

  • Create and execute queries by using a compute solution that leverages SQL serverless and Spark cluster
  • Recommend and implement Azure Synapse Analytics database templates
  • Push new or updated data lineage to Microsoft Purview
  • Browse and search metadata in Microsoft Purview Data Catalog

Ingest and transform data • Design and implement incremental loads • Transform data by using Apache Spark • Transform data by using Transact-SQL (T-SQL) in Azure Synapse Analytics • Ingest and transform data by using Azure Synapse Pipelines or Azure Data Factory • Transform data by using Azure Stream Analytics • Cleanse data • Handle duplicate data • Avoiding duplicate data by using Azure Stream Analytics Exactly Once Delivery • Handle missing data • Handle late-arriving data • Split data • Shred JSON • Encode and decode data • Configure error handling for a transformation • Normalize and denormalize data • Perform data exploratory analysis

  • Design and implement incremental loads
  • Transform data by using Apache Spark
  • Transform data by using Transact-SQL (T-SQL) in Azure Synapse Analytics
  • Ingest and transform data by using Azure Synapse Pipelines or Azure Data Factory
  • Transform data by using Azure Stream Analytics
  • Cleanse data
  • Handle duplicate data
  • Avoiding duplicate data by using Azure Stream Analytics Exactly Once Delivery
  • Handle missing data
  • Handle late-arriving data
  • Split data
  • Shred JSON
  • Encode and decode data
  • Configure error handling for a transformation
  • Normalize and denormalize data
  • Perform data exploratory analysis

Develop a batch processing solution

  • Develop batch processing solutions by using Azure Data Lake Storage, Azure Databricks, Azure Synapse Analytics, and Azure Data Factory
  • Use PolyBase to load data to a SQL pool
  • Implement Azure Synapse Link and query the replicated data
  • Create data pipelines
  • Scale resources
  • Configure the batch size
  • Create tests for data pipelines
  • Integrate Jupyter or Python notebooks into a data pipeline
  • Upsert data
  • Revert data to a previous state
  • Configure exception handling
  • Configure batch retention
  • Read from and write to a delta lake

Develop a stream processing solution

  • Create a stream processing solution by using Stream Analytics and Azure Event Hubs
  • Process data by using Spark structured streaming
  • Create windowed aggregates
  • Handle schema drift
  • Process time series data
  • Process data across partitions
  • Process within one partition
  • Configure checkpoints and watermarking during processing
  • Scale resources
  • Create tests for data pipelines
  • Optimize pipelines for analytical or transactional purposes
  • Handle interruptions
  • Configure exception handling
  • Upsert data
  • Replay archived stream data

Manage batches and pipelines

  • Trigger batches
  • Handle failed batch loads
  • Validate batch loads
  • Manage data pipelines in Azure Data Factory or Azure Synapse Pipelines
  • Schedule data pipelines in Data Factory or Azure Synapse Pipelines
  • Implement version control for pipeline artifacts
  • Manage Spark jobs in a pipeline

Implement data security

  • Implement data masking
  • Encrypt data at rest and in motion
  • Implement row-level and column-level security
  • Implement Azure role-based access control (RBAC)
  • Implement POSIX-like access control lists (ACLs) for Data Lake Storage Gen2
  • Implement a data retention policy
  • Implement secure endpoints (private and public)
  • Implement resource tokens in Azure Databricks
  • Load a DataFrame with sensitive information
  • Write encrypted data to tables or Parquet files
  • Manage sensitive information

Monitor data storage and data processing

  • Implement logging used by Azure Monitor
  • Configure monitoring services
  • Monitor stream processing
  • Measure performance of data movement
  • Monitor and update statistics about data across a system
  • Monitor data pipeline performance
  • Measure query performance
  • Schedule and monitor pipeline tests
  • Interpret Azure Monitor metrics and logs
  • Implement a pipeline alert strategy

Optimize and troubleshoot data storage and data processing

  • Compact small files
  • Handle skew in data
  • Handle data spill
  • Optimize resource management
  • Tune queries by using indexers
  • Tune queries by using cache
  • Troubleshoot a failed Spark job
  • Troubleshoot a failed pipeline run, including activities executed in external services

Certification

    • By earning DP-203 certification, you can become Microsoft Certified Azure Data Engineer
    • Demonstrate abilities to Design and implement data storage, data processing and data security features
    • On successful completion of DP-203: Data Engineering on Microsoft Azure training aspirants receive a Course Completion Certificate from us
    • By successfully clearing the DP-203 exams, aspirants earn Microsoft Certification

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Reviews

A
Asif Ali

Excellent training sessions provided by CloudThat. I have attended a few webinars on Microsoft Azure and the trainers are really knowledgeable with good real time experience on Azure Cloud. The materials and the test prep kit along with the interactive training sessions really helps in clearing the certification exams. I would recommend everyone who is looking to make a career in cloud domain to register for the trainings provided by CloudThat.

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Jawed Akhtar

I had attend the Microsoft Azure training today.it was so good and nice to explain very clearly and it was really helpful for my upcoming professional careers.

R
Remya Ravi

Great and valuable training session. Thank you.

Frequently Asked Questions

Yes, the DP-203 exam has a time limit of approximately 120 minutes (2 hours). During this time, you will need to answer questions related to Azure Data Platform.

The DP-203 exam covers various topics related to Azure Data Platform. The exam may include questions on data storage, analysis and data ingestion, data integration, security implementation, performance optimization, deployment, and more.

The passing score for the DP-203 exam may vary and is subject to change. Currently, it is 70% (700 marks out of 1000). For the most current information on passing scores, it is advisable to consult the official Microsoft certification website.

DP-203 certification is valid for one year. Within that period, you may need to renew the certification by passing the renewal assessment, which is free.

The DP-203 certification validates your expertise in designing and implementing solutions using Azure Data Platform. This can expand your career prospects and increase your earning potential as an Azure Data Engineer.

To register for the DP-203 exam, follow these steps. Firstly, visit the Microsoft Learning website and search for the DP-203 exam. Then, click on the exam link to access the exam details page. On the exam details page, click the "Schedule Exam" or "Register" button. Upon redirection, you will reach the Microsoft Certification dashboard, where you have the option to either sign in using your existing Microsoft account or create a new account. Once signed in, you can select a test center or opt for an online proctored exam, choose a convenient date and time, and proceed with the payment process. After the registration, you will receive a confirmation email with further instructions for the exam day.

The DP-203 certification can benefit various job roles within data industry. It is particularly beneficial for professionals aiming for career advancement in roles such as data engineer, data scientist, data analyst, data architect, database administrator, and more. The responsibilities of these individuals encompass the design and implementation of solutions using Azure Data Platform, working in collaboration with stakeholders, analyzing data, creating visualizations, and optimizing data solutions. The DP-900 certification validates their expertise, enhances their credibility, and opens opportunities for higher-level roles and increased responsibilities in organizations that leverage the Azure Data Platform for data-driven decision-making and process automation.

Attaining the DP-203 certification as a Microsoft Data Engineer can have a substantial impact on career progression and an increase in salary. The certification validates your expertise in designing and implementing solutions using Azure Data Platform, positioning you as a highly sought-after professional in the industry and reinforcing your credibility in the field.

Undoubtedly! Besides the DP-203 certification, there are numerous other certifications available that pertain to the Azure Data Platform. Some notable ones include – DP 100, DP 420, DP 300, DP 500 etc. These certifications provide targeted validation of specialized skills within the Azure Data Platform. They enhance your career prospects in roles such as data analyst, data engineer, data scientist, and more, depending on your specific area of expertise and interest. It's important to note that the above FAQs provide general information. For the most accurate and up-to-date information, it's recommended to refer to the official Microsoft certification website or consult with Microsoft Learning resources.

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