Data Engineering Best Practices Using Azure Data Factory by Microsoft (Recordings)

Data Engineering Best Practices Using Azure Data Factory by Microsoft (Recordings)

$299.00

Use 50% Discount Code: DPS50 (Now: US$ 299 . After Discount: US$ 149.5)

Data Engineering Best Practices Using Azure Data Factory

Speakers: Abhishek Narain, Sunil Sabat, Linda Wang

8-hrs Virtual Classroom Training
LIVE Attendance + Class Recordings

Abstract: In this workshop, we will cover data engineering best practices while using Azure Data Factory – Performance, Security, and Scalability being the key focus areas. We will build ETL pipelines as part of the workshop for hands-on learning.

Modules

1. Data pipeline overview

  • What is data factory?
  • Data engineering common scenario
  • Getting started and environment setup

2. Data Integration: Connectivity and code-free transformation

  • Bringing data to data lake on Azure: On-premises and SaaS/PaaS datastore connectivity with a Copy activity
  • Transforming data using data flows

3. Best practices for operationalizing data pipelines

  • Govern data using Azure Purview Integration
  • Scalability and Performance considerations
  • Security
  • External integrations with compute engines (Databricks, SProc)
  • Continuous Integration and Continuous Deployment (CICD)

PS: This class will be recorded and the registered attendee will get 12 months of streaming access to the recorded class. The recordings will be available within 30 days of class completion.

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8-hrs Virtual Classroom Training
LIVE Attendance + Class Recordings

Description

Data Engineering Best Practices Using Azure Data Factory

Abstract: In this workshop, we will cover data engineering best practices while using Azure Data Factory – Performance, Security, and Scalability being the key focus areas. We will build ETL pipelines as part of the workshop for hands-on learning.

Modules:

1. Data pipeline overview

  • What is data factory?
  • Data engineering common scenario
  • Getting started and environment setup

2. Data Integration: Connectivity and code-free transformation

  • Bringing data to data lake on Azure: On-premises and SaaS/PaaS datastore connectivity with a Copy activity
  • Transforming data using data flows

3. Best practices for operationalizing data pipelines

  • Govern data using Azure Purview Integration
  • Scalability and Performance considerations
  • Security
  • External integrations with compute engines (Databricks, SProc)
  • Continuous Integration and Continuous Deployment (CICD)

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