Microsoft Azure Data Factory Certification Training Course

24 hours of robust learning program

Course diverged into 10 distinct modules

Develop skills in creating and managing data pipelines

Manageable instalment payment options

Blended online & classroom learning options

4.85/5

6676 Enrolled

Overview

Skills we aim to impart:

Understand data integration workflows
Design data transformation with Data Flow
Use and Utilise mapping Data Flows
Learn to configure linked services and datasets
Implement data movement activities
Monitor and troubleshoot data pipelines
Handle security & access control in ADF

Learning Objectives

By completing the course, you will master these skills:

Understand the fundamentals of Azure Data Factory and its role in data integration and orchestration

Design and implement data pipelines using Azure Data Factory

Learn how to efficiently integrate and transform data from various sources, including on-premises and cloud-based systems

Develop skills in using Azure Data Factory to orchestrate complex data workflows and schedule data movement activities

Gain knowledge of advanced features of Azure Data Factory, such as data partitioning, dynamic content and data flow transformations

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Prerequisites

To enrol in the Microsoft Azure Data Factory Certification Training, the following prerequisites are recommended:

Working knowledge of challenges related to the design and implementation of data warehouses, data lakes, factories, and stream analytics in Azure SQL Data Warehouse and Azure Data Factory
Proficiency in using business intelligence tools effectively, as it is a crucial skill set in data integration and analytics
Strong familiarity and expertise in PowerShell with Azure, allowing seamless navigation and utilization of Azure resources
Several years of hands-on experience in data integration, showcasing a solid understanding of data management and integration principles
Extensive experience working with Azure DBaaS (Database-as-a-Service) platforms over several years, demonstrating a deep understanding of Azure's database offerings

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We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

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Curriculum

Working knowledge of challenges related to the design and implementation of data warehouses, data lakes, factories, and stream analytics in Azure SQL Data Warehouse and Azure Data Factory.
Proficiency in using business intelligence tools effectively, as it is a crucial skill set in data integration and analytics.
Strong familiarity and expertise in PowerShell with Azure, allowing seamless navigation and utilization of Azure resources.
Several years of hands-on experience in data integration, showcasing a solid understanding of data management and integration principles.
Extensive experience working with Azure DBaaS (Database-as-a-Service) platforms over several years, demonstrating a deep understanding of Azure's database offerings.

Overview of Data Warehousing
Consideration for Data Warehouse Solution
Lab-- Exploring a Data Warehousing Solution

Difference between On-Prem and On-Cloud
Resources that can help to calculate Compute and Storage
Lab-- How to use Azure Calculator for Planning Infrastructure

Data Warehouse Design Overview
Designing Dimension Tables
Designing Fact Tables
Physical Design for a Data Warehouse
Lab-- Implementing a Data Warehouse

Introduction to Columnstore Indexes
Creating Columnstore Indexes
Working with Columnstore Indexes
Lab-- Using Columnstore Indexes

Copying Data with the Azure Data Factory
Lab-- Implement an Azure SQL Data Warehouse
Advantages of Azure SQL Data Warehouse
Implementing an Azure SQL Data Warehouse Database
Developing an Azure SQL Data Warehouse
Migrating to an Azure SQL Data Warehouse

Overview of Azure Data Factory
Explain the data factory process and Components
Setup Azure Data Factory
Lab-- Setup Azure Data Factory on Microsoft Azure Cloud

Create linked Services
Create the Datasets
Create Activities and Pipelines
Manage Integration Runtime
Lab-- Practical demo for all the components

Copy Data Tool
Copy Activity in Pipeline
Copy Data from on-prem to the cloud
Incremental SQL DB single table
Incremental SQL DB multiple tables

Copy from SQL DB to Synapse SQL Pools
Bulk Copy Multiple Tables
Code-Free Data Transformation at Scale
Azure Databricks Notebook Activity
Control Flow in Azure Data Factory

Introduction to Business Intelligence
Introduction to Data Analysis
Introduction to Reporting

Frequently asked questions

Microsoft Azure Data Factory Training is a globally known credential in cloud computing that provides professionals with proficiency in designing and implementing data pipelines using Azure Data Factory. This training is certified by Microsoft. It benefits individuals who wish to build their cloud computing careers. Some of these benefits are:

1. Master ETL processes
2. Enhance cloud integration skills
3. Understand real-time data analytics
4. Stay competitive with industry-relevant skills
5. Improved career opportunities

Several candidates can enrol in our training and obtain Azure Data Factory Certification. These candidates must be interested in advancing their careers in cloud computing. It is intended for professionals who want to become Data Integration Specialist. The ideal candidates are the following:

1. Data engineers
2. Data analysts
3. Cloud architects
4. IT professionals

To enrol in the Azure Data Factory Training, there are several eligibility criteria required by the professionals. It is recommended that you have a basic working knowledge of some criteria and fulfil them before entering this course. These are as follows:

Working knowledge of challenges related to the design and implementation of data warehouses, data lakes, factories and stream analytics in Azure Data Factory
Proficiency in using business intelligence tools effectively, as it is a crucial skill set in data integration and analytics
Strong familiarity and expertise in PowerShell with Azure, allowing seamless navigation and utilization of Azure resources
Several years of hands-on experience in data integration, showcasing a solid understanding of data management and integration principles
Extensive experience working with Azure DBaaS (Database-as-a-Service) platforms over several years, demonstrating a deep understanding of Azure's database offerings

Azure Data Factory is one of the leading cloud computing areas, and the demand for professionals with expertise in handling data pipelines and data lakes is increasing. By attending this course, an individual can gain the knowledge needed to pursue a career as a Data Integration Specialist, Cloud Data Architect or ETL Developer.

Yes, Azure Data Factory seamlessly integrates with various Azure services like Azure SQL Database, Azure Blob Storage and more. It also supports encryption to ensure data security and custom code and scripting options like Python, C#, and SQL for advanced data transformations.

An individual will learn several skills and abilities in the cloud computing domain from our Microsoft Azure Data Factory Training. The enrolled candidates can utilise these skills to orchestrate complex data workflows and schedule data movement using Azure data factory. Some of these skills are:

1. Develop advanced data integration workflows
2. Learn to enhance the performance of data pipelines
3. Master the use of Azure-hosted and SSIS integration runtimes
4. Utilise Mapping and Wrangling Data Flows
5. Implement solutions for real-time data ingestion
6. Connect and integrate cloud-based data sources

There are several key topics related to cloud computing and implementing Azure data factory covered in our training. These subjects are taught by our expert instructors through practical training sessions across 10 separate modules. Some of these topics are as follows:

1. Introduction to Azure Data Factory
2. Data Integration Fundamentals
3. Creating and Managing Pipelines
4. Data Flow Transformations
5. Data Integration Runtime
6. Connecting to Data Sources
7. Parameterization and Dynamic Content
8. Triggers and Scheduling Pipelines