Introduction to Data Engineering from Coursera

Start your journey in one of the fastest growing professions today with this beginner-friendly Data Engineering course! You will be introduced to the core concepts, processes, and tools you need to know in order to get a foundational knowledge of data engineering. as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in the ecosystem.

You will begin this course by understanding what is data engineering as well as the roles that Data Engineers, Data Scientists, and Data Analysts play in this exciting field. Next you will learn about the data engineering ecosystem, the different types of data structures, file formats, sources of data, and the languages data professionals use in their day-to-day tasks.

You will become familiar with the components of a data platform and gain an understanding of several different types of data repositories such as Relational (RDBMS) and NoSQL databases, Data Warehouses, Data Marts, Data Lakes and Data Lakehouses. You’ll then learn about Big Data processing tools like Apache Hadoop and Spark. You will also become familiar with ETL, ELT, Data Pipelines and Data Integration.

This course provides you with an understanding of a typical Data Engineering lifecycle which includes architecting data platforms, designing data stores, and gathering, importing, wrangling, querying, and analyzing data. You will also learn about security, governance, and compliance.

You will learn about career opportunities in the field of Data Engineering and the different paths that you can take for getting skilled as a Data Engineer. You will hear from several experienced Data Engineers, sharing their insights and advice.

By the end of this course, you will also have completed several hands-on labs and worked with a relational database, loaded data into the database, and performed some basic querying operations.

What's inside

Syllabus

What is Data Engineering?

In this module, you will learn about the different entities that come together to form a modern data ecosystem and the role Data Engineers, Data Scientists, Data Analysts, Business Analysts, and Business Intelligence Analysts play in this ecosystem. You will learn what data engineering is and the key tasks in a data engineering lifecycle. You will also gain an understanding of the responsibilities of a data engineer, the skillsets they need in order to be successful, and what a typical day in the life of a data engineer looks like.

The Data Engineering Ecosystem

In this module, you will learn about the data engineering ecosystem, the different types of data structures, file formats, sources of data, and the languages data professionals use in their day-to-day tasks. You will gain an understanding of several different types of data repositories such as relational and non-relational databases, data warehouses, data marts, and data lakes. You will learn about ETL and ELT processes, data pipelines, and data integration platforms. You will also gain an understanding of what big data is, and the tools used for processing and storing big data. At the end of this module, you will be guided to create an IBM Cloud account, and provision an instance of IBM Db2.

Data Engineering Lifecycle

In this module, we will walk you through the data engineering lifecycle. You will learn about the architecture of a data platform, factors for selecting and designing data stores, and the different facets of security as it applies to data platforms and data lifecycle management. You will also learn about the process, steps, and tools used for gathering, importing, wrangling, and querying data. You will gain an understanding of performance monitoring and the steps you can take to troubleshoot performance issues. We will also talk about governance regulations, why we need them, and how technology enables compliance to regulations. During the course of this module, you will be guided to load data from a CSV file into the IBM Db2 instance you created in the previous module. You will also be guided to explore your dataset using some basic SQL queries that will be provided to you.

Career Opportunities and Data Engineering in Action

In this module, you will learn about career opportunities in the field of Data Engineering and the different paths that you can take for getting skilled as a Data Engineer. At the end of the module, you will be presented with the final graded assignment which is divided into two parts. The first part of the final assignment includes a couple of quiz questions and the second part includes open-ended questions that will be reviewed and graded by a peer.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Introduces learners to the core concepts of data engineering, providing a foundational knowledge

Provides an overview of roles and responsibilities in data engineering, data science, and data analytics

Covers the data engineering ecosystem, including various data structures, file formats, and data sources used in the industry

Explores data repositories such as relational databases, NoSQL databases, data warehouses, data marts, data lakes, and data lakehouses

Introduces big data processing tools like Apache Hadoop and Spark

Provides hands-on labs to practice data loading, querying, and wrangling tasks

Reviews summary

Data engineering institute

learners say this course gives beginners a broad overview of what data engineering entails. Students learn about data ingestion, processing, pipelines, and data repositories. Real-world examples and hands-on exercises featuring IBM DB2 services provide practical experience. Industry experts share their perspectives on the field, giving students insights into the roles and responsibilities of data engineers. However, some reviewers note that the course can be repetitive and that the hands-on labs may not always work. Overall, this course is highly recommended for those looking to start a career in data engineering or gain a better understanding of the field.

This course provides a comprehensive overview of data engineering, making it suitable for beginners with little to no background in the field.

"Really good overview for beginner to have a taste what is Data Engineering is"

"This course gave me appropriate materials to learn basic skill on data engineer"

"I enjoyed this module. I got a broad overview of what data engineering entails."

"This course is optimal for the foundations and understanding of Data Engineering."

The course includes videos featuring industry experts who share their perspectives on the field, providing students with insights into the roles and responsibilities of data engineers.

"The viewpoints from data professionals complements the educational content very well"

"Great overall! The viewpoints from data professionals complements the educational content very well and gives the student a much better idea of what the process is to become a data engineer."

"The participation of experts was crucial to have a very realistic idea of the market and what must be done to become a Data Engineer."

"This course is really great for peoples, who wants to learn a foundations of data engeeniring."

Hands-on exercises and real-world examples using IBM DB2 services provide students with practical experience in data engineering techniques.

"IBM’s Cloud Db2 rounds up the task by providing first hands-on experience."

"This course nicely covered the basics of Data Engineering and helped me understand Data Engineering in an excellent way through examples and hands-on lab activities.Thanks,IBM"

"Very informative and I like the usage of the IBM DB2 services as hands on labs."

"This was a great overview course. After completing it, I really understood how data is used and moved."

Some reviewers note that the course can be repetitive and that the hands-on labs may not always work.

"It was a great course. It has been very well designed so we can learn easily and understand all the topics about data engineering."

"This is the very basic conecept that is tackled by this course, yet I still gain new insights from it."

"This course is really great for peoples, who wants to learn a foundations of data engeeniring."

"The course worked well at the very beginning process (first two weeks)."

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 Introduction to Data Engineering with these activities:

Compile Learning Material

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Increase retention of concepts by breaking down notes, assignments, quizzes, and other materials into a concise compilation

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Review lecture materials and notes
Organize and group related topics
Summarize and consolidate information
Include diagrams, charts, or other visuals

Explore Apache Spark and its applications in data engineering

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Familiarize yourself with the capabilities of Apache Spark and its role in data engineering by following guided tutorials and exercises.

Browse courses on Apache Spark

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Install Apache Spark on your local machine
Learn the basics of Spark programming using PySpark
Apply Spark to perform data transformations, aggregations, and machine learning tasks
Explore Spark's ecosystem, including Spark SQL and Spark Streaming

Guided Tutorials: Apache Hadoop and Spark

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Reinforce the concepts of Apache Hadoop and Spark through step-by-step guided tutorials

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Enroll in online tutorials or courses
Follow step-by-step instructions
Build small projects using Hadoop and Spark
Experiment with different configurations

Nine other activities

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Concurrent: Follow tutorials on data engineering tools

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Enhance your understanding of data engineering tools and technologies by following guided tutorials to familiarize yourself with their capabilities and applications.

Browse courses on Apache Hadoop

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Find tutorials on Apache Hadoop and Apache Spark, two popular big data processing frameworks.
Work through the tutorials to gain hands-on experience with these tools.
Explore how these tools can be used to solve real-world data engineering challenges.

Concurrent: Join a study group or online forum

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Enhance your learning experience by joining a study group or participating in online forums related to data engineering, allowing you to connect with peers, share knowledge, and get support.

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Identify and join a study group or online forum dedicated to data engineering.
Participate in discussions, ask questions, and share your insights with other learners.
Collaborate on projects or assignments to reinforce your understanding.

Concurrent: Practice SQL queries

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Strengthen your SQL skills by practicing writing queries to extract and manipulate data from databases, which is essential for data engineering tasks.

Browse courses on SQL Queries

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Find online resources or platforms that offer SQL practice exercises.
Solve a variety of SQL queries, covering different levels of complexity.
Review your solutions and identify areas for improvement.

Attend Data Engineering Workshops

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Gain hands-on experience and interact with experts in the field of Data Engineering

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Research and identify relevant workshops
Register and attend workshops
Participate in hands-on exercises
Network with industry professionals

Design a data pipeline

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Applying your knowledge of data engineering processes, design a data pipeline that meets specific requirements for data ingestion, transformation, and delivery.

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Define the requirements of the data pipeline
Design the architecture of the data pipeline
Implement the data pipeline using appropriate tools and technologies
Test and evaluate the performance of the data pipeline
Document the data pipeline for future reference

Practice Data Pipelines and ETL

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Gain proficiency in Data Pipelines and ETL through repetitive exercises and drills

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Set up a data integration tool
Extract data from diverse sources
Transform and clean data
Load data into target systems

Practice solving data engineering challenges

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Sharpen your problem-solving skills and reinforce your understanding of data engineering concepts by practicing with real-world data engineering challenges.

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Identify and collect data engineering challenges
Develop and implement solutions to address the challenges
Evaluate the effectiveness and efficiency of your solutions
Compare your solutions with others and learn from different approaches

Build a Mini Data Engineering Project

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Apply your acquired knowledge by designing and implementing a small-scale Data Engineering project

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Choose a project idea that aligns with the course content
Gather the necessary data
Design and implement a data pipeline
Analyze and visualize the results

Post-course: Build a data pipeline

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Apply your acquired knowledge and skills by building a data pipeline project, which involves designing and implementing a system for extracting, transforming, and loading data.

Browse courses on Data Pipelines

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Define the scope and objectives of your data pipeline project.
Choose appropriate data sources and data engineering tools.
Design and implement data extraction, transformation, and loading processes.
Test and deploy your data pipeline.
Monitor and maintain your data pipeline to ensure its efficiency and accuracy.

Career center

Learners who complete Introduction to Data Engineering will develop knowledge and skills that may be useful to these careers:

Data Engineer

Data Engineers are responsible for designing, building, and maintaining data platforms that store, process, and analyze data. They work closely with data scientists and data analysts to ensure that the data is accurate, reliable, and accessible. This course provides a foundational knowledge of data engineering, including the core concepts, processes, and tools used in the field. It also covers the roles that Data Engineers, Data Scientists, and Data Analysts play in the data ecosystem.

See salaries and explore the career path for Data Engineer

Data Scientist

Data Scientists use data to solve business problems. They work with data engineers to access and analyze data, and they develop models and algorithms to predict outcomes and make recommendations. This course provides a foundational knowledge of data engineering, which is essential for Data Scientists who want to be able to work with data effectively.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts use data to identify trends and patterns. They work with data engineers and data scientists to analyze data and develop insights that can help businesses make better decisions. This course provides a foundational knowledge of data engineering, which is essential for Data Analysts who want to be able to work with data effectively.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts work with businesses to identify and solve problems. They use data to analyze business processes and make recommendations for improvement. This course provides a foundational knowledge of data engineering, which can be helpful for Business Analysts who want to be able to work with data more effectively.

See salaries and explore the career path for Business Analyst

Database Administrator

Database Administrators are responsible for managing and maintaining databases. They work with data engineers to ensure that databases are performant and reliable. This course provides a foundational knowledge of data engineering, which is essential for Database Administrators who want to be able to work with databases effectively.

See salaries and explore the career path for Database Administrator

Business Intelligence Analyst

Business Intelligence Analysts use data to identify trends and patterns. They work with businesses to develop and implement strategies for improving business performance. This course provides a foundational knowledge of data engineering, which can be helpful for Business Intelligence Analysts who want to be able to work with data more effectively.

See salaries and explore the career path for Business Intelligence Analyst

Data Security Analyst

Data Security Analysts develop and implement policies and procedures for protecting data security. They work with data engineers to ensure that data is used in a compliant and ethical manner. This course provides a foundational knowledge of data engineering, which is essential for Data Security Analysts who want to be able to work with data effectively.

See salaries and explore the career path for Data Security Analyst

Machine Learning Engineer

Machine Learning Engineers design, develop, and maintain machine learning models. They work with data engineers to access and analyze data, and they develop models that can predict outcomes and make recommendations. This course provides a foundational knowledge of data engineering, which is essential for Machine Learning Engineers who want to be able to work with data effectively.

See salaries and explore the career path for Machine Learning Engineer

Big Data Analyst

Big Data Analysts work with large datasets to identify trends and patterns. They use data to develop insights that can help businesses make better decisions. This course provides a foundational knowledge of data engineering, which is essential for Big Data Analysts who want to be able to work with big data effectively.

See salaries and explore the career path for Big Data Analyst

Data Architect

Data Architects design and build data platforms. They work with data engineers to ensure that data platforms are scalable, reliable, and secure. This course provides a foundational knowledge of data engineering, which is essential for Data Architects who want to be able to work with data effectively.

See salaries and explore the career path for Data Architect

DevOps Engineer

DevOps Engineers work to bridge the gap between development and operations teams. They use data to identify and resolve issues that can affect the performance of data platforms. This course provides a foundational knowledge of data engineering, which can be helpful for DevOps Engineers who want to be able to work with data more effectively.

See salaries and explore the career path for DevOps Engineer

Cloud Engineer

Cloud Engineers design, build, and maintain cloud computing environments. They work with data engineers to deploy data platforms in the cloud. This course provides a foundational knowledge of data engineering, which can be helpful for Cloud Engineers who want to be able to work with data more effectively.

See salaries and explore the career path for Cloud Engineer

Data Governance Analyst

Data Governance Analysts develop and implement policies and procedures for managing data. They work with data engineers to ensure that data is used in a compliant and ethical manner. This course provides a foundational knowledge of data engineering, which is essential for Data Governance Analysts who want to be able to work with data effectively.

See salaries and explore the career path for Data Governance Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. They work with data engineers to integrate data into software applications. This course provides a foundational knowledge of data engineering, which can be helpful for Software Engineers who want to be able to work with data more effectively.

See salaries and explore the career path for Software Engineer

Data Privacy Analyst

Data Privacy Analysts develop and implement policies and procedures for protecting data privacy. They work with data engineers to ensure that data is used in a compliant and ethical manner. This course provides a foundational knowledge of data engineering, which is essential for Data Privacy Analysts who want to be able to work with data effectively.

See salaries and explore the career path for Data Privacy Analyst