Data Engineering Capstone Project from Coursera

Showcase your skills in this Data Engineering project! In this course you will apply a variety of data engineering skills and techniques you have learned as part of the previous courses in the IBM Data Engineering Professional Certificate.

You will demonstrate your knowledge of Data Engineering by assuming the role of a Junior Data Engineer who has recently joined an organization and be presented with a real-world use case that requires architecting and implementing a data analytics platform.

In this Capstone project you will complete numerous hands-on labs. You will create and query data repositories using relational and NoSQL databases such as MySQL and MongoDB. You’ll also design and populate a data warehouse using PostgreSQL and IBM Db2 and write queries to perform Cube and Rollup operations.

You will generate reports from the data in the data warehouse and build a dashboard using Cognos Analytics. You will also show your proficiency in Extract, Transform, and Load (ETL) processes by creating data pipelines for moving data from different repositories. You will perform big data analytics using Apache Spark to make predictions with the help of a machine learning model.

This course is the final course in the IBM Data Engineering Professional Certificate. It is recommended that you complete all the previous courses in this Professional Certificate before starting this course.

What's inside

Syllabus

Data Platform Architecture and OLTP Database

In this module, you will design a data platform that uses MySQL as an OLTP database. You will be using MySQL to store the OLTP data.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Significant emphasis on hands-on labs for a more practical learning experience

Covers industry-standard technologies such as MySQL, MongoDB, and Apache Spark

Provides a comprehensive overview of data engineering processes, from data acquisition to data analysis

Offers the opportunity to build a data analytics dashboard using Cognos Analytics

Requires prior knowledge in data engineering concepts and tools

Does not provide a comprehensive introduction to big data concepts and technologies

Reviews summary

Practical data engineering capstone

According to learners, the Data Engineering Capstone Project is a valuable course for consolidating skills acquired in the IBM Data Engineering Professional Certificate. Students highlight its hands-on labs and practical, real-world project structure as particularly beneficial for building a portfolio. The course provides a comprehensive overview of data engineering components, integrating various databases, ETL processes, and big data tools like Apache Spark. However, a significant number of learners report frequent issues with outdated or buggy lab environments and unclear setup instructions, leading to considerable time spent on troubleshooting. The peer review system is also noted as a less effective method for technical feedback. While its practical application is largely praised, be prepared for technical hurdles.

Integrates various data engineering tools and processes.

"The integration of various databases (SQL/NoSQL), ETL processes, and even a bit of ML with Spark made it very comprehensive."

"This course is a true gem for aspiring data engineers. It integrates all the key components: databases, ETL, big data, and even reporting."

"Overall, a valuable capstone... it provided a holistic view of a data engineering project from start to finish."

Offers hands-on experience applying data engineering concepts.

"This capstone project was a great way to tie everything together... The hands-on labs were very practical..."

"Absolutely brilliant! The project structure is challenging but incredibly rewarding."

"It really solidified my understanding of the entire data pipeline. I found the problem-solving aspect very useful for preparing for real-world scenarios."

The peer review process is often seen as unhelpful.

"The peer review system is also not ideal for a technical course like this."

"The peer review system is also terrible for evaluating technical projects."

"My experience with the peer review wasn't helpful for specific technical feedback."

Some instructions lack detail, especially for setup.

"The instructions for setting up the environments could be a bit clearer, and some parts felt rushed."

"The instruction quality is mediocre, often just telling you what to type without explaining the 'why'."

"I found some areas, especially around Db2 and Cognos, felt a bit superficial given the breadth of topics."

Technical issues and outdated setups frequently impede progress.

"I found the labs to be frequently outdated, leading to many errors and requiring significant troubleshooting outside the course."

"Disappointing. Many labs have broken links or depend on outdated versions of software. I spent more time debugging environment issues."

"My biggest issue was with the hands-on labs. They were often buggy, and the support in the forums was slow or non-existent."

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 Data Engineering Capstone Project with these activities:

Review data modeling concepts

Show steps

Refresh your knowledge of data modeling techniques, including entity-relationship diagrams, normalization, and data warehousing principles, to enhance your ability to design and implement efficient data structures.

Browse courses on Data Modeling

Show steps

Review textbooks or online resources on data modeling
Practice creating ER diagrams for simple scenarios
Discuss data modeling concepts with peers or mentors

Review MySQL basics

Show steps

Solidify your understanding of MySQL, a foundational skill for data engineering.

Browse courses on MySQL

Show steps

Review SQL queries and commands
Practice creating and modifying tables
Execute queries to retrieve and manipulate data

Practice RDBMS querying

Show steps

Sharpen your SQL skills by practicing queries on sample databases, focusing on data retrieval, manipulation, and aggregation techniques commonly used in data engineering.

Browse courses on MySQL

Show steps

Find sample databases online or create your own
Use a database management tool or command-line interface to connect to the database
Write SQL queries to perform data retrieval, filtering, sorting, and aggregation

Ten other activities

Expand to see all activities and additional details

Show all 13 activities

Participate in peer review sessions

Show steps

Engage with fellow learners to review and provide feedback on each other's work, fostering a collaborative learning environment and improving your problem-solving and communication skills.

Show steps

Find a study group or online forum for peer review
Share your work with others and seek feedback
Review and provide constructive criticism on others' work

Consolidate and organize course materials

Show steps

Organize your notes, assignments, and other course materials into a central repository, making them easily accessible for review and reference, improving your ability to retain and retrieve information effectively.

Show steps

Gather all relevant course materials
Create a structured filing system or digital notebook
Categorize and label materials for easy retrieval

Explore MongoDB documentation

Show steps

Enhance your understanding of MongoDB by exploring its comprehensive documentation.

Browse courses on MongoDB

Show steps

Read tutorials on data modeling and query optimization
Follow examples of aggregation and indexing techniques

Solve data warehousing exercises

Show steps

Reinforce your data warehousing concepts by solving practical exercises.

Browse courses on Data Warehousing

Show steps

Design star and snowflake schemas
Create tables and load data
Write queries to analyze data

Review Apache Spark for beginners

Show steps

Review the basics of Apache Spark, including its architecture, components, and programming interfaces, to strengthen your understanding of big data processing.

Browse courses on Apache Spark

Show steps

Watch beginner-friendly tutorials on Apache Spark
Install Apache Spark on your local machine
Write basic Spark programs using PySpark or Scala

Build a simple data pipeline using Python

Show steps

Create a working data pipeline using Python to demonstrate your understanding of data ingestion, transformation, and loading processes, providing hands-on experience with real-world data handling scenarios.

Browse courses on Data Pipelines

Show steps

Choose a data source and define the data transformation rules
Write Python code to implement the data pipeline using libraries like Pandas and NumPy
Test and validate the pipeline using sample data

Solve practice problems on data analysis and visualization

Show steps

Engage in practice drills and exercises to strengthen your data analysis and visualization skills, improving your ability to interpret data, identify patterns, and communicate insights effectively.

Browse courses on Data Analysis

Show steps

Find practice problems and datasets online or in textbooks
Use data analysis tools like Python, R, or Tableau to solve the problems
Compare your solutions with others or discuss them with mentors

Build a dashboard using Cognos Analytics

Show steps

Apply your data engineering skills by creating a visually informative dashboard.

Browse courses on Data Visualization

Show steps

Connect to data sources and create data sets
Design visualizations and reports
Configure interactive features

Develop an ETL pipeline

Show steps

Demonstrate your ability to build a complete ETL pipeline by integrating data from multiple sources.

Browse courses on ETL

Show steps

Design the ETL architecture
Implement data extraction and transformation
Load data into the target system
Configure monitoring and error handling

Participate in a data analytics hackathon

Show steps

Challenge yourself and showcase your skills by participating in a data analytics competition.

Browse courses on Big Data Analytics

Show steps

Form a team or work independently
Analyze the provided data set
Develop a solution using appropriate techniques
Submit your results and prepare for presentation

Career center

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

Data Engineer

As a Data Engineer, you will be responsible for designing, building, and maintaining data platforms and pipelines. You will work with data from a variety of sources, including relational databases, NoSQL databases, and big data sources. This course will help you build a strong foundation in data engineering principles and practices. You will learn how to design and implement data platforms, perform data analytics, and build data pipelines.This course is recommended for anyone who wants to pursue a career as a Data Engineer.

See salaries and explore the career path for Data Engineer

Data Warehouse Architect

As a Data Warehouse Architect, you will be responsible for designing and implementing data warehouses. You will work with data from a variety of sources, including relational databases, NoSQL databases, and big data sources. This course will help you build a strong foundation in data warehouse design and implementation. You will learn how to design and implement data warehouses that are scalable, reliable, and performant.

See salaries and explore the career path for Data Warehouse Architect

Data Analyst

As a Data Analyst, you will be responsible for collecting, cleaning, and analyzing data. You will use data to identify trends, patterns, and insights. This course will help you build a strong foundation in data analysis principles and practices. You will learn how to collect, clean, and analyze data, and how to present your findings in a clear and concise way.

See salaries and explore the career path for Data Analyst

Data Scientist

As a Data Scientist, you will be responsible for using data to solve business problems. You will use data to build models that can predict future outcomes, identify risks, and optimize business processes. This course will help you build a strong foundation in data science principles and practices. You will learn how to use data to build models, and how to evaluate and interpret the results of your models.

See salaries and explore the career path for Data Scientist

Business Intelligence Analyst

As a Business Intelligence Analyst, you will be responsible for using data to improve business decision-making. You will work with data to identify trends, patterns, and insights. This course will help you build a strong foundation in business intelligence principles and practices. You will learn how to use data to identify trends, patterns, and insights, and how to present your findings in a clear and concise way.

See salaries and explore the career path for Business Intelligence Analyst

Database Administrator

As a Database Administrator, you will be responsible for managing and maintaining databases. You will ensure that databases are available, performant, and secure. This course will help you build a strong foundation in database administration principles and practices. You will learn how to install, configure, and manage databases.

See salaries and explore the career path for Database Administrator

Software Engineer

As a Software Engineer, you will be responsible for designing, developing, and maintaining software applications. This course may be useful for you if you are interested in developing software applications that use data. You will learn how to design and develop software applications that are scalable, reliable, and performant.

See salaries and explore the career path for Software Engineer

IT Manager

As an IT Manager, you will be responsible for managing and overseeing an IT department. This course may be useful for you if you are interested in managing an IT department that uses data. You will learn how to manage and oversee an IT department that is efficient and effective.

See salaries and explore the career path for IT Manager

Project Manager

As a Project Manager, you will be responsible for planning, executing, and closing projects. This course may be useful for you if you are interested in managing projects that use data. You will learn how to plan, execute, and close projects that are successful.

See salaries and explore the career path for Project Manager

Data Architect

As a Data Architect, you will be responsible for designing and implementing data architectures. This course may be useful for you if you are interested in designing and implementing data architectures that use data. You will learn how to design and implement data architectures that are scalable, reliable, and performant.

See salaries and explore the career path for Data Architect

Technical Writer

As a Technical Writer, you will be responsible for creating and maintaining technical documentation. This course may be useful for you if you are interested in creating and maintaining technical documentation for software applications that use data. You will learn how to create and maintain technical documentation that is clear, concise, and accurate.

See salaries and explore the career path for Technical Writer

Quality Assurance Analyst

As a Quality Assurance Analyst, you will be responsible for testing and evaluating software applications. This course may be useful for you if you are interested in testing and evaluating software applications that use data. You will learn how to test and evaluate software applications for defects and errors.

See salaries and explore the career path for Quality Assurance Analyst

Information Security Analyst

As an Information Security Analyst, you will be responsible for protecting information systems from security threats. This course may be useful for you if you are interested in protecting information systems from security threats that use data. You will learn how to protect information systems from security threats.

See salaries and explore the career path for Information Security Analyst

Data Governance Analyst

As a Data Governance Analyst, you will be responsible for developing and implementing data governance policies. This course may be useful for you if you are interested in developing and implementing data governance policies for data. You will learn how to develop and implement data governance policies that are effective and efficient.

See salaries and explore the career path for Data Governance Analyst

Data Privacy Analyst

As a Data Privacy Analyst, you will be responsible for protecting personal data from unauthorized access and use. This course may be useful for you if you are interested in protecting personal data from unauthorized access and use. You will learn how to protect personal data from unauthorized access and use.

See salaries and explore the career path for Data Privacy Analyst