Created By Eshant Garg
Learning Objectives: Gain in-depth knowledge of the structure and certification objectives of DP-203 to excel as an Azure Data Engineer. Learn strategies to maximize Azure's free tier for 12 months.
Learning Objectives: Become a proficient Azure user and Data Engineer by mastering Azure Subscription creation, resource management, and budgeting; exploring Data Engineer's role and technologies; and developing skills in ML modeling and deployment with FastAPI and MLOps.
Learning Objectives: Master Azure Storage Services, provisioning, redundancy, access tiers, File Share and Disk Storage. Explore Cosmos DB, Data Lake evolution. Compare Blob Storage and Data Lake, examine security. Differentiate HA and DR concepts, explore HA/DR options for Azure Storage and Cosmos DB.
Learning Objectives: Acquire comprehensive expertise in Azure SQL and Synapse Analytics, including their features, architecture comparison, pool creation, data analysis, and security measures such as data masking and encryption.
Learning Objectives: Master the fundamentals of Azure Data Factory and Azure Databricks, including their features, provisioning, data access, data processing, Spark Basics, cluster exploration, and other essential components.
Learning Objectives: Master Azure Stream Analytics and Windowing Functions for real-time data processing. Learn to configure input and output, use different window types (Tumbling, Hopping, Sliding, and Session), and process Blob Storage and IOT Hub Input.
Learning Objectives: Master the implementation of Azure Monitor service to efficiently monitor and optimize various Azure resources, including Blob and Data Lake Storage, Azure Synapse Analytics, and Cosmos DB.
Learning Objectives: Learn to effectively monitor and optimize Data Factory pipelines, Azure Databricks for big data analytics, and Stream Analytics for real-time data processing using various monitoring tools like metrics, alerts, and diagnostic settings.
Learning Objectives: Learn to troubleshoot and optimize data processing in various Azure services, including Data Lake Storage, Stream Analytics, and Azure Synapse Analytics. Also, gain proficiency in managing the Data Lifecycle to ensure data quality and compliance.
Learning Objectives: Master data solutions in Azure: data types, storage options, Azure store selection, recovery planning, CosmosDB vs. Data Lake vs. Blob Storage design, SQL Database vs. Data warehouse, Batch Processing with Data Factory and DataBricks, Data Ingestion Methods, Real-Time Processing, Compute Resources, Lambda Architecture, and secure endpoint planning.
In this final module, we will provide a comprehensive recap of the Microsoft Azure Data Engineer (DP-203) Course, highlighting how it equips you with practical skills for the real world.
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Yes, you will experience KnowledgeHut's immersive learning in an on-demand format. This will include e-learning material to help you:
Yes, our online course is designed to give you flexibility to skill up as per your convenience. The course is delivered in a Self-Paced mode so that you can balance your work and learning as per your schedule.
Yes! Upon passing this online course, you will receive a signed certificate of completion from KnowledgeHut. Thousands of KnowledgeHut alumni use their course certificate to demonstrate skills to employers and their networks.
More than the certificate, however, you will get to showcase your newly acquired skills by working on real-world projects and adding these to your portfolio. KnowledgeHut’s online courses is well-regarded by industry experts, who contribute to our curriculum and use our tech programs to train their own teams.
You can cancel your enrolment and receive refunds in line with our Cancellations and Refunds policy found at https://www.knowledgehut.com/refund-policy.
Yes, it does! In the unlikely event that you are not satisfied with the course, and you wish to withdraw within the first seven days, we’ll issue a 100% refund. Refer to our Online Self-Paced Courses Refund Policy for more details.
