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Marcelo Pastorino

With over 2.5 quintillion bytes of data generated each day, you need to rely on modern tools to efficiently use and analyze data. In this course, you will learn how to leverage the power of Azure to create data integration pipelines in the cloud.

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With over 2.5 quintillion bytes of data generated each day, you need to rely on modern tools to efficiently use and analyze data. In this course, you will learn how to leverage the power of Azure to create data integration pipelines in the cloud.

Data-driven decision making is the path to business success. In this course, Integrating Data in Microsoft Azure, you will gain foundational knowledge to integrate data utilizing the power of Microsoft Azure.

First, you will learn how to migrate data from on-premise and Amazon Web Services to Azure. Next, you will discover how to easily construct ETL processes and create data integration pipelines using Azure Data Factory.

Finally, you will explore how to create a real-time pipeline, to ingest and process real-time events sent by IoT devices using Azure EventHubs, Azure Stream Analytics, and Power BI.

When you’re finished with this course, you will have the skills and knowledge needed to create data integration pipelines using some of the great tools that are part of the Azure ecosystem.

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What's inside

Syllabus

Course Overview
Data Integration Services on Azure
Migrate On-premises Data to Azure SQL Server
Migrate Data from Amazon S3 to Azure Blob Storage
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Create Data Pipelines with Azure Data Factory Copy Data Tool
Create Data Pipelines with Azure Data Factory
Create Real-time Data Pipelines with Azure EventHubs and Azure Stream Analytics
Real-time Monitoring with Power BI

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Uses Azure Data Factory, which is widely recognized in data integration
Builds a strong foundation for using Azure for data integration
Develops skills in data migration, ETL processes, and real-time data pipelines
Taught by Marcelo Pastorino, an instructor with expertise in data integration on Azure
Requires familiarity with Azure and basic data integration concepts
May require additional resources for hands-on practice

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Integrating Data in Microsoft Azure with these activities:
Organize your course materials
Organize all the materials for this course to make your learning journey easier.
Show steps
  • Create a folder or binder for your course materials.
  • Print out or download all the course materials.
  • Organize the materials into sections or topics.
Review data modeling concepts
Review the fundamental concepts of data modeling to strengthen your foundation for this course.
Browse courses on Data Modeling
Show steps
  • Read the textbook chapter on data modeling.
  • Review your notes from previous data modeling courses.
  • Complete practice problems on data modeling.
Review Azure Data Storage Concepts
Review the fundamental concepts of data storage in Azure to strengthen your foundation for this course.
Show steps
  • Read the Azure documentation on data storage services.
  • Review the Azure Blob Storage documentation.
  • Review the Azure File Storage documentation.
  • Review the Azure Database Storage documentation.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Create an Azure Data Lake using the Azure CLI
Follow a tutorial to create an Azure Data Lake using the Azure CLI to gain hands-on experience with Azure data storage.
Browse courses on Azure Data Lake
Show steps
  • Find a tutorial on creating an Azure Data Lake using the Azure CLI.
  • Set up the Azure CLI and create an Azure Data Lake.
  • Explore the Azure Data Lake using the Azure CLI.
Load data into Azure Blob Storage using various methods
Practice loading data into Azure Blob Storage using different methods to improve your data handling skills.
Browse courses on Azure Blob Storage
Show steps
  • Review the different methods for loading data into Azure Blob Storage.
  • Use the Azure Data Factory to load data into Azure Blob Storage.
  • Use the Azure CLI to load data into Azure Blob Storage.
  • Compare the performance and efficiency of different data loading methods.
Contribute to an open-source data integration project
Contribute to an open-source data integration project to gain practical experience and connect with the community.
Browse courses on Data Integration
Show steps
  • Find an open-source data integration project that interests you.
  • Review the project's documentation and codebase.
  • Identify an area where you can contribute.
  • Submit a pull request with your contribution.
Design an ETL pipeline using Azure Data Factory
Create an ETL pipeline using Azure Data Factory to demonstrate your understanding of data integration in Azure.
Browse courses on Azure Data Factory
Show steps
  • Define the data sources and destination for your ETL pipeline.
  • Design the data transformations and cleansing processes.
  • Create the Azure Data Factory pipeline using the Azure portal.
  • Test and deploy the ETL pipeline.
Participate in a data integration hackathon
Participate in a data integration hackathon to showcase your skills and learn from other experts in the field.
Browse courses on Data Integration
Show steps
  • Find a data integration hackathon that aligns with your interests.
  • Form a team or work individually.
  • Develop a solution that addresses the hackathon challenge.
  • Present your solution to a panel of judges.

Career center

Learners who complete Integrating Data in Microsoft Azure will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and insights. This course can help Data Analysts build foundational knowledge in data integration with Microsoft Azure.
Data Engineer
Data Engineers design and build data pipelines to integrate data from disparate sources, making it accessible for analysis and decision-making. This course would provide a foundation in data integration with Azure.
Database Administrator
A Database Administrator is someone who plans, installs, configures, and maintains databases. Databases are essential to every modern organization for storing every kind of data you can imagine. As an Azure-certified professional with skills in data integration, you will be well-prepared to analyze data and design databases for maximum efficiency.
Business Intelligence Analyst
Business Intelligence Analysts use data analysis to support decision-making at the business level. Courses on data integration in Azure can be useful for learning about data sources and data analysis methods.
Data Scientist
Data Scientists use data and analytics to solve business problems. A course on data integration in Azure would be useful for building foundational knowledge in data integration techniques using Azure technologies.
Solution Architect
Solution Architects design and implement technical solutions to meet business needs. A course on data integration in Azure would provide foundational knowledge for designing and implementing data-driven solutions using Azure technologies.
Cloud Architect
Cloud Architects design, build, and maintain cloud computing systems. This course on data integration in Azure would provide foundational knowledge needed to build and manage data pipelines for Azure.
Software Engineer
Software Engineers are responsible for designing, developing, and maintaining software systems. Skills in data integration with in Azure would be useful for developing data-driven applications.
Technical Lead
Technical Leads guide and mentor technical teams. They also ensure that projects are completed on time and within budget. Experience in data integration with Azure would be useful for Technical Leads managing data-driven projects.
Systems Analyst
Systems Analysts analyze and design business systems. A course on data integration in Azure would be useful for learning about data integration techniques and technologies.
Project Manager
Project Managers plan, execute, and close projects. They also manage project teams and resources. A course in data integration in Azure can be useful for Project Managers working with data-driven projects.
IT Architect
IT Architects design and manage the technical infrastructure of an organization. An understanding of Azure data integration could be useful for designing and managing data-driven IT infrastructure.
Data Architect
Data Architects design and maintain data management systems, ensuring that data is organized, accessible, and secure. A course on data integration through Microsoft Azure may be useful for learning how to build and manage Azure-based data pipelines.
Web Developer
Web Developers design and develop websites and web applications. An understanding of data integration techniques in Azure would be useful for developing data-driven web applications.
Information Security Analyst
Information Security Analysts plan and implement security measures to protect an organization's data and information systems. A course on data integration in Azure may be useful for understanding how to secure data in the cloud.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Integrating Data in Microsoft Azure.
Provides a comprehensive overview of data integration, covering the key concepts, tools, and techniques involved in building and managing data integration solutions.
Provides a comprehensive overview of data warehousing fundamentals, covering the key concepts, tools, and techniques involved in building and managing data warehouses.
Provides a comprehensive overview of data mining, covering the key concepts, tools, and techniques involved in building and managing data mining solutions.
Provides a comprehensive guide to machine learning with Python, covering the key concepts, tools, and techniques involved in building and managing machine learning solutions.

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