Monitoring Microsoft Azure Data Pipelines and Processing from Pluralsight

Data pipelines and processes transform raw data into meaningful insights for organizations that can drive future business direction. This course explores how to monitor the pipelines and the processes within to ensure accurate and timely insights.

Organizations need to get business insights from multiple, disparate sources and it is important that the pipelines and processes that enable this insight are healthy. In this course, Monitoring Microsoft Azure Data Pipelines and Processing, you will learn foundational knowledge of the core structure of data pipeline services and how to monitor them. First, you will examine the foundation of data pipelines and processes. Next, you will discover how to monitor Azure Data Factory as a control flow solution. Finally, you will explore how to monitor the HDInsight and Databricks data flow solution. When you’re finished with this course, you will have the skills and knowledge of monitoring data pipelines and processes needed to ensure the health and accuracy of generated business insights.

What's inside

Syllabus

Course Overview

Data Pipeline Exploration

Implementing Monitoring for Data Factory

Implementing HDInsight Monitoring

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores data pipelines and processing, which are core concepts in data science and analytics

Covers monitoring Microsoft Azure Data Pipelines and Processing, which is a specific and in-demand area in cloud computing

Provides foundational knowledge of the core structure of data pipeline services, which is essential for effective monitoring

Utilizes hands-on labs and interactive materials, which enhance the learning experience and promote practical skills development

Taught by John Savill, who is recognized for their expertise in data pipeline monitoring

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 Monitoring Microsoft Azure Data Pipelines and Processing with these activities:

Refresh your coding skills in Python

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This activity will help you ensure that your coding skills are up to date, which is essential for working with data pipelines.

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Review Python basics and syntax
Practice writing Python code for data manipulation tasks
Complete coding challenges or exercises to test your skills

Follow a guided tutorial on Azure Data Factory

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This activity will provide you with hands-on experience in using Azure Data Factory, which is a key tool for data pipeline management.

Browse courses on Azure Data Factory

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Find a well-regarded online tutorial on Azure Data Factory
Follow the tutorial steps to create a data pipeline
Experiment with different configurations and settings
Troubleshoot any issues you encounter

Practice troubleshooting common data pipeline issues

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This activity will help you develop your problem-solving skills by practicing how to identify and resolve common issues that arise in data pipelines.

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Identify common data pipeline issues and their symptoms
Practice troubleshooting these issues using real-world examples
Document the solutions to these issues for future reference

Three other activities

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Mentor or tutor other students on data pipeline concepts

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This activity will help you reinforce your understanding of data pipeline concepts by explaining them to others and answering their questions.

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Identify opportunities to mentor or tutor other students
Prepare materials to support your teaching
Engage with students, answer their questions, and provide guidance

Create a data pipeline monitoring dashboard

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This activity will allow you to apply your knowledge of data pipeline monitoring by creating a custom dashboard for visualizing key metrics.

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Identify the key metrics you want to monitor
Choose a data visualization tool or platform
Configure the dashboard to display the metrics in a clear and concise way
Share the dashboard with your team or stakeholders

Develop a data pipeline for a specific business scenario

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This project-based activity will provide you with a comprehensive understanding of the data pipeline development process, from requirements gathering to deployment.

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Define the business scenario and requirements
Design and implement the data pipeline using Azure Data Factory or other tools
Monitor and maintain the pipeline to ensure its performance and reliability
Evaluate the results and identify areas for improvement

Career center

Learners who complete Monitoring Microsoft Azure Data Pipelines and Processing will develop knowledge and skills that may be useful to these careers:

Data Engineer

Data Engineers are responsible for designing, building, and maintaining the infrastructure and processes that transform raw data into meaningful insights. This course on Monitoring Microsoft Azure Data Pipelines and Processing can help build a foundation for a career as a Data Engineer by providing knowledge of the core structure of data pipeline services and how to monitor them. This knowledge is essential for ensuring the accuracy and timeliness of the insights generated by data pipelines and processes.

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Business Analyst

Business Analysts work with businesses to identify and solve problems. They use data to understand the business and to make recommendations for improvements. This course on Monitoring Microsoft Azure Data Pipelines and Processing may be useful for Business Analysts who want to gain a better understanding of how data pipelines and processes work. This knowledge can help them to better understand the data they are working with and to make more accurate and informed recommendations.

See salaries and explore the career path for Business Analyst

Data Scientist

Data Scientists use data to build models and algorithms that can solve business problems. They work with data engineers and data analysts to gather, clean, and analyze data. This course on Monitoring Microsoft Azure Data Pipelines and Processing may be useful for Data Scientists who want to gain a better understanding of how data pipelines and processes work. This knowledge can help them to better understand the data they are working with and to build more accurate and effective models.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts use data to solve business problems and make informed decisions. They gather, clean, and analyze data to identify trends and patterns. This course on Monitoring Microsoft Azure Data Pipelines and Processing may be useful for Data Analysts who want to gain a better understanding of how data pipelines and processes work. This knowledge can help them to better understand the data they are working with and to make more accurate and informed decisions.

See salaries and explore the career path for Data Analyst

Cloud Architect

Cloud Architects design and manage cloud computing systems. They work with data engineers and data scientists to build and maintain the infrastructure and processes that transform raw data into meaningful insights. This course on Monitoring Microsoft Azure Data Pipelines and Processing may be useful for Cloud Architects who want to gain a better understanding of how data pipelines and processes work. This knowledge can help them to design and manage more efficient and effective cloud computing systems.

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Data Governance Manager

Data Governance Managers oversee the governance of an organization's data. They are responsible for developing and implementing policies and procedures to ensure that the data is accurate, accessible, and secure. This course on Monitoring Microsoft Azure Data Pipelines and Processing may be useful for Data Governance Managers who want to gain a better understanding of how data pipelines and processes work. This knowledge can help them to better develop and implement policies and procedures to ensure the governance of the organization's data.

See salaries and explore the career path for Data Governance Manager

IT Manager

IT Managers oversee the IT department of an organization. They are responsible for planning, implementing, and managing the organization's IT systems. This course on Monitoring Microsoft Azure Data Pipelines and Processing may be useful for IT Managers who want to gain a better understanding of how data pipelines and processes work. This knowledge can help them to better manage and implement the organization's IT systems.

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Database Administrator

Database Administrators manage and maintain databases. They work with data engineers and data scientists to ensure that the data is accurate and accessible. This course on Monitoring Microsoft Azure Data Pipelines and Processing may be useful for Database Administrators who want to gain a better understanding of how data pipelines and processes work. This knowledge can help them to better manage and maintain databases.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They work with data engineers and data scientists to build and maintain the infrastructure and processes that transform raw data into meaningful insights. This course on Monitoring Microsoft Azure Data Pipelines and Processing may be useful for Software Engineers who want to gain a better understanding of how data pipelines and processes work. This knowledge can help them to build more efficient and effective software applications.

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Statistician

Statisticians collect, analyze, and interpret data. They work with data engineers and data scientists to develop and implement strategies to ensure that the organization's data is used effectively.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve business problems. They work with data engineers and data scientists to develop and implement strategies to ensure that the organization's data is used effectively.

See salaries and explore the career path for Operations Research Analyst

Data Architect

Data Architects design and build the architecture of an organization's data systems. They work with data engineers and data scientists to develop and implement strategies to ensure that the organization's data is used effectively.

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Machine Learning Engineer

Machine Learning Engineers design and build machine learning models. They work with data engineers and data scientists to develop and implement strategies to ensure that the organization's data is used effectively.

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Epidemiologist

Epidemiologists investigate the causes and spread of disease. They work with data engineers and data scientists to develop and implement strategies to ensure that the organization's data is used effectively.

See salaries and explore the career path for Epidemiologist

Chief Data Officer

Chief Data Officers are responsible for overseeing the organization's data strategy. They work with data engineers, data scientists, and other stakeholders to develop and implement strategies to ensure that the organization's data is used effectively.

See salaries and explore the career path for Chief Data Officer

Monitoring Microsoft Azure Data Pipelines and Processing

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