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Microsoft Azure Data Fundamentals

ONLC Training Centers @ 2 Park Ave, New York, NY & Virtually Online

Unlock the power of data with hands-on training in cloud-based data solutions. Learn the essentials of data storage, processing, and security to enhance your analytical skills and drive strategic decision-making.

(7) All levels 18 and older
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Azure Data Engineering Training

  • Advanced
  • 18 and older
  • $2,990
  • Earn 29,900 reward points
  • Price Lock Guarantee
  • 1601 Broadway, New York, NY
  • 30 hours over 4 sessions

Start Dates (0)

  • $2,990
  • 30 hours over 4 sessions
  • Course 8595
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Class Description

Description

What you'll learn in this azure training:

In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. 

The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.

You Will Learn How To:

  • Explore compute and storage options for data engineering workloads in Azure.
  • Run interactive queries using serverless SQL pools.
  • Perform data Exploration and Transformation in Azure Databricks.
  • Explore, transform, and load data into the Data Warehouse using Apache Spark.
  • Ingest and load Data into the Data Warehouse.
  • Transform Data with Azure Data Factory or Azure Synapse Pipelines.
  • Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines.
  • Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link.
  • Perform end-to-end security with Azure Synapse Analytics.
  • Perform real-time Stream Processing with Stream Analytics.
  • Create a Stream Processing Solution with Event Hubs and Azure Databricks.
  • Continue learning and face new challenges with after-course one-on-one instructor coaching.

Training Prerequisites

Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. Specifically completing:

  • Learning Tree course 8566, Microsoft Azure Fundamentals Training (AZ-900T00)
  • Learning Tree course 8586, Microsoft Azure Data Fundamentals Training (DP-900)

Certification Information

  • This class does prepare an individual to take the Microsoft Certified Exam DP-203.

Course Outline:

  • Module 1: Introduction to data engineering on Azure
  • Module 2: Introduction to Azure Data Lake Storage Gen2
  • Module 3: Introduction to Azure Synapse Analytics
  • Module 4: Use Azure Synapse serverless SQL pool to query files in a data lake
  • Module 5: Use Azure Synapse serverless SQL pools to transform data in a data lake
  • Module 6: Create a lake database in Azure Synapse Analytics
  • Module 7: Analyze data with Apache Spark in Azure Synapse Analytics
  • Module 8: Transform data with Spark in Azure Synapse Analytics
  • Module 9: Use Delta Lake in Azure Synapse Analytics
  • Module 10: Analyze data in a relational data warehouse
  • Module 11: Load data into a relational data warehouse
  • Module 12: Build a data pipeline in Azure Synapse Analytics
  • Module 13: Use Spark Notebooks in an Azure Synapse Pipeline
  • Module 14: Plan hybrid transactional and analytical processing using Azure Synapse Analytics
  • Module 15: Implement Azure Synapse Link with Azure Cosmos DB
  • Module 16: Implement Azure Synapse Link for SQL
  • Module 17: Get started with Azure Stream Analytics
  • Module 18: Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics
  • Module 19: Visualize real-time data with Azure Stream Analytics and Power BI
  • Module 20: Introduction to Microsoft Purview
  • Module 21: Integrate Microsoft Purview and Azure Synapse Analytics
  • Module 22: Explore Azure Databricks
  • Module 23: Use Apache Spark in Azure Databricks
  • Module 24: Run Azure Databricks Notebooks with Azure Data Factory

Refund Policy

If a customer would like to cancel or transfer their course, they must notify Coursehorse prior to 3 weeks before the start date of the course or within seven days of registration. On-Demand Courses cannot be cancelled once purchased and are not eligible for refund.

  • If a customer transfers to another course prior to 3 weeks before the start date or within seven days of registration of the course in which originally enrolled, 100% of any prepaid course tuition will be applied toward the course tuition for the subsequent course.
  • If a customer needs to cancel an enrollment 3 weeks prior to the start of the class or within seven days of registration, we will refund 95% of any prepaid course tuition for that enrollment.
  • If a customer does need to transfer or cancel a course within 3 weeks of the start date of the course or after seven days from the date of registration, a fee equal to 50% of the price of the course will be assessed for any standard attendances.

Attendances associated with a Learning Tree program will be assessed a $500 fee. Training Passports, Training Vouchers and Pay-As-You-Learn Vouchers cannot be used after their expiration dates, and a course cancellation or transfer by the customer will not extend a Training Passport, Training Voucher Pack or Pay-As-You-Learn Voucher Pack expiration date.

In the event that an instructor or the school needs to cancel at the last minute, students will receive a refund less a 5% non-refundable registration fee.

In any event where a customer wants to cancel their enrollment and is eligible for a full refund, a 5% processing fee will be deducted from the refund amount.

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Learning Tree International

Established in 1974, Learning Tree International is a leading provider of IT training and management training to business and government organizations worldwide. In addition, Learning Tree provides IT Workforce Optimization Solutions – a modern approach that improves the adoption of skills, and accelerates...

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