IT & Software > IT Certifications
20 h
£34.99 Free
Master Azure Data Engineering: DP-203 Certification Guaranteed
What you will learn:
- Master the Microsoft Certified: Azure Data Engineer Associate (DP-203) certification exam.
- Gain hands-on experience with core Azure data services.
- Design and implement robust and scalable data storage solutions.
- Develop efficient and reliable data processing pipelines.
- Secure your data using industry best practices and Azure security features.
- Monitor and optimize your data infrastructure for peak performance.
- Implement effective data governance strategies with Microsoft Purview.
- Become proficient in using Azure Data Lake Storage Gen2, Azure SQL Database, Cosmos DB, Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure Event Hubs, and Azure Stream Analytics.
- Prepare thoroughly for the DP-203 exam with extensive practice questions.
- Launch a successful career as a cloud data engineer.
Description
Ace the Microsoft Certified: Azure Data Engineer Associate (DP-203) exam with our expertly designed training program. This isn't just another course; it's your pathway to a lucrative career in cloud data engineering.
We cover every facet of the DP-203 exam objectives, offering a deep dive into designing, implementing, securing, monitoring, and optimizing data storage and processing solutions within the Azure ecosystem.
Here's what sets us apart:
- Structured Learning Path: We progress logically through key concepts, building your expertise step-by-step.
- Hands-On Labs: Get your hands dirty with practical exercises and real-world scenarios, solidifying your understanding.
- In-depth Coverage: Master Azure Data Lake Storage Gen2, Azure SQL Database, Cosmos DB, Azure Synapse Analytics (including Spark pools and serverless SQL pools), Azure Data Factory, Azure Databricks, Azure Event Hubs, and Azure Stream Analytics.
- Security Best Practices: Learn how to safeguard your data using Azure's robust security features and policies.
- Performance Optimization: Discover advanced techniques for monitoring and fine-tuning your data pipelines for peak performance.
- Data Governance: Explore Data Governance practices using Microsoft Purview.
- Extensive Practice Exams: Sharpen your skills and boost your confidence with 500+ practice questions designed to mirror the actual exam.
Course Structure:
We begin with foundational cloud and Azure concepts before delving into the core areas of data storage design, data processing development, security measures, performance optimization, and finally, a rigorous exam preparation phase to ensure your success. Enroll now and transform your career!
Curriculum
Segment1-Introduction and Setup
This introductory segment lays the groundwork for your Azure data engineering journey. Lectures cover cloud computing fundamentals, an overview of Microsoft Azure, exam-taking strategies, and hands-on setup of an Azure account and navigation of the Azure portal. You'll also receive guidance on successfully completing the entire course.
Segment2-Design and implement data storage-DataLake
This section focuses on Azure Data Lake Storage Gen2. You'll learn about different types of Azure storage accounts, create a Data Lake Gen2 storage account, and practice uploading files in various formats. This hands-on approach ensures you understand the core concepts.
Segment3-Design and implement data storage-Azure SQL Server
This segment delves into Azure SQL Database, covering pricing tiers, configurations, creation, and connection using SSMS and Azure Data Studio. Extensive hands-on exercises cover T-SQL fundamentals, including select statements, conditional logic, aggregate functions, grouping, window functions (LEAD/LAG), CTEs, and CASE statements, providing a solid foundation in SQL.
Segment4-Design and implement data storage-CosmosDB
Explore the capabilities of Cosmos DB, covering use cases, pricing models, throughput, APIs, data modeling, and practical implementation. Hands-on exercises guide you through account creation, database and container creation, item management, partition strategies, consistency levels, and global scaling.
Segment5-Design and implement data storage-Azure Synapse Analytics
This in-depth section covers Azure Synapse Analytics, its components, and compute power. You will learn the differences between SQL Database and SQL Data Warehouse, explore serverless SQL pools, and learn about dedicated SQL pools. Hands-on labs cover workspace creation, querying data from Data Lake, data loading methods (Polybase, COPY INTO), schema design (OLAP/OLTP, fact/dimension tables), table distribution strategies, index use, partitioning and switching, restore points, and database templates.
Segment6-Develop data processing-Azure Synapse Spark Pool
This segment introduces Apache Spark and its benefits. You will learn about Spark pools in Azure Synapse, and through hands-on exercises, create a Spark pool, work with dataframes using Python, read data from Data Lake, use loading functions, and write data to Dedicated SQL using Spark pools.
Segment7-Develop data processing-Azure Data Factory
Master Azure Data Factory (ADF) with this comprehensive section. Lectures cover ETL processes, hands-on creation of ADF instances, copy data activities, pipelines, mapping data flows (including debugging and sink types), integration runtimes (including self-hosted IR), triggers, Git integration and version control.
Segment8-Develop data processing-Azure DataBricks
Learn the fundamentals of Azure Databricks, exploring its benefits and capabilities. Hands-on labs cover workspace creation, compute cluster setup, data reading (DBFS, ADLS), visualizations, JSON data processing, data saving (Databricks tables, Data Lake), stream processing, writing data to Synapse SQL, delta tables, job scheduling, and integrating Databricks notebooks with ADF pipelines.
Segment9-Develop data processing-Azure Event Hubs
This segment covers Azure Event Hubs, focusing on the differences between batch and stream data processing. Hands-on labs include creating an Event Hub namespace, ingesting and capturing data.
Segment10-Develop data processing-Stream Analytics
Master real-time data processing with Azure Stream Analytics. You'll learn about costing, create a Stream Analytics workspace, define inputs and outputs (Synapse SQL), formulate queries, handle errors, utilize window functions (tumbling, hopping, sliding, session, snapshot), use reference data, and monitor jobs.
Segment11-Secure-Azure Data Lake Security Aspects
This segment explores security in Azure Data Lake Gen2. You will learn about authentication, authorization, RBAC roles, ACLs, and securing storage using service endpoints. Hands-on exercises include using Azure Data Explorer, connecting storage accounts with different methods, creating Microsoft Entra ID users, assigning RBAC roles, implementing ACLs, and configuring service endpoints.
Segment12-Azure Synapse Analytics Security Aspects
This section covers security in Azure Synapse Analytics. You'll learn about encryption types, setting up transparent data encryption using Key Vault, using managed identities, implementing column-level security, dynamic data masking, and row-level security. Hands-on labs cover key vault setup, managed identity configuration, and security policy implementation.
Segment13-DataFactory and Databricks Security Aspects
Learn to secure Azure Data Factory and Azure Databricks. Hands-on exercises will cover encrypting Data Factory, using secret scopes and key vaults for secure credential management in Databricks notebooks, and implementing scoped credentials for managing access.
Segment14-Monitor and Optimize-Data Lake Storage
This section covers monitoring and optimizing Azure Data Lake Storage. Learn about access tiers and lifecycle management rules. Hands-on labs include changing tiers at the file level and configuring lifecycle management.
Segment15-Monitor and Optimize-Azure Data Factory
Learn to monitor and debug Azure Data Factory pipelines. Hands-on exercises include using annotations, monitoring services, creating alerts, and monitoring logs via Log Analytics.
Segment16-Monitor and Optimize-Synapse Analytics
Learn how to monitor and optimize Azure Synapse Analytics. You will use DMV commands, explore workload management, result set caching, check data skewness, and connect Synapse with Log Analytics. Hands-on exercises will guide you through these processes.
Segment17-Monitor and Optimize-Stream Analytics, Cosmos DB
Learn to monitor Azure Stream Analytics and Cosmos DB. You'll cover streaming units, event partitioning, time handling, and monitoring using built-in tools. Hands-on labs include monitoring jobs and setting up Log Analytics integration for Cosmos DB.
Segment18-Monitor and Optimize-Data Governance with Microsoft Purview
Learn to use Microsoft Purview for data governance and management. Hands-on exercises cover creating a Purview account, scanning data assets (Data Lake, Synapse SQL pool), browsing Purview, connecting Data Factory, and removing assets.
Segment19-Practice Papers-500 Questions
This final segment provides 500 practice exam questions to solidify your knowledge and prepare you for the DP-203 certification exam. The questions are designed to mimic the actual exam environment to ensure your success.
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