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This course features interactive videos to help you understand both the analytical concepts and the software. This course contains a capstone project, in which you will apply the concepts taught using a separate data source; this realistic project gives learners the practice and confidence necessary to connect, explore, and analyze data sources into the future.This course is also part of a certificate:

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This course features interactive videos to help you understand both the analytical concepts and the software. This course contains a capstone project, in which you will apply the concepts taught using a separate data source; this realistic project gives learners the practice and confidence necessary to connect, explore, and analyze data sources into the future.This course is also part of a certificate:

Data Analytics and Visualization Certificate

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What's inside

Learning objective

By first learning how important databases are to acquiring and storing data, you can then become familiar with the common database structure, the star schema, and learn the techniques of joining data from multiple tables. finally, learn how to write reporting queries and to build complex scripts for processing data. by the end of the course, you will have enough practice in writing sql to evaluate and analyze a database that they will be ready to use their skills in a business setting.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
By learning both the analytical concepts and the software used, you can enhance your understanding of data analysis and visualization
Through the capstone project, you can apply the concepts you learn to a real-world data source, providing valuable practical experience
This course forms part of a certificate in Data Analytics and Visualization, indicating a comprehensive approach to the subject matter
The emphasis on SQL skills prepares learners for data analysis and evaluation tasks in a business context

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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 Data Engineering with these activities:
Review basic SQL syntax
Review the basic syntax of SQL to prepare for the course
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Show steps
  • Go over SQL commands for data definition
  • Review SQL commands for data retrieval
Compile Course Materials
Organize and review key course materials to enhance understanding and retention.
Show steps
  • Gather lecture notes, presentations, and assignments
  • Create a structured system for organizing materials
  • Review and highlight important concepts
Refresh Knowledge on Databases
Reinforce your understanding of databases before the course begins to ensure a solid foundation.
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Show steps
  • Review the concepts of a database, database management system, and database models
  • Practice creating and managing tables, columns, and indexes
  • Execute basic SQL queries to retrieve and manipulate data
13 other activities
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Solve SQL exercises from Leetcode
Practice writing and executing SQL queries to improve your understanding of database structure and query syntax.
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Show steps
  • Create a Leetcode account
  • Select the SQL section
  • Solve easy and medium level SQL exercises
  • Review solutions and explanations
Complete SQL tutorials
Complete online tutorials to practice writing SQL queries
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Show steps
  • Find tutorials on a reputable online learning platform
  • Follow the tutorials step-by-step
  • Complete the exercises and quizzes provided in the tutorials
Follow Online Tutorials
Supplement your learning by exploring online tutorials that provide additional insights and practical examples.
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Show steps
  • Identify reputable online platforms and resources
  • Choose tutorials that align with specific course topics
  • Follow the tutorials step-by-step and complete any practice exercises
Collaborate with Others in Study Groups
Enhance learning by collaborating with classmates for in-depth discussions of topics, exercises, and assignments and provide support to each other.
Show steps
  • Identify classmates with shared interests
  • Schedule regular group meetings
  • Set a clear agenda and goals
  • Contribute actively to discussions
  • Provide constructive feedback and mutual support
Join Study Groups
Collaborate with peers to discuss course concepts, solve problems, and reinforce understanding.
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Show steps
  • Connect with classmates and form study groups
  • Establish regular meeting times
  • Review course materials together and work through practice problems
Solve SQL practice problems
Solve SQL practice problems to reinforce understanding
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Show steps
  • Find a website or textbook with SQL practice problems
  • Attempt to solve the problems on your own
  • Check your answers against the provided solutions
SQL Practice Drills
巩固你的SQL技能,通过练习解决常见数据处理问题。
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Show steps
  • Complete coding exercises on writing SELECT, INSERT, UPDATE, and DELETE queries
  • Practice using aggregate functions (e.g., SUM(), COUNT(), AVG())
  • Solve data manipulation challenges using JOINs
  • Optimize queries for improved performance
Build a data dashboard for a mock business
Create an interactive data dashboard that visualizes and summarizes key metrics for a mock business, applying the skills learned in the course.
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Show steps
  • Define the business scenario and identify key metrics
  • Gather and clean data
  • Choose a data visualization tool
  • Design and build the dashboard
  • Present and share the dashboard
Attend Data Analytics Workshops
Participate in workshops to gain practical experience, learn from industry experts, and network with professionals.
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Show steps
  • Research and identify relevant workshops in your area
  • Register for workshops that align with your learning goals
  • Attend workshops, actively participate in discussions, and engage with speakers
  • Follow up with speakers and attendees to expand your network
Connect with Mentors
Seek guidance and support from experienced professionals in the field to enhance your understanding and career prospects.
Show steps
  • Identify potential mentors through networking events, industry contacts, or online platforms
  • Reach out to mentors and express your interest in their guidance
  • Establish regular communication and seek advice on course-related topics, career development, and industry trends
Build a small SQL project
Create a small SQL project to apply your skills and deepen your understanding
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Show steps
  • Identify a small dataset that you can use for your project
  • Design a database schema for your project
  • Create a database and populate it with your data
  • Write SQL queries to analyze your data and generate insights
Data Analysis Project
Apply the concepts and techniques learned in the course to a real-world data analysis project.
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Show steps
  • Define the problem statement and gather relevant data
  • Clean and prepare the data for analysis
  • Perform data analysis using SQL and visualization tools
  • Develop insights and recommendations based on the analysis
  • Present the findings in a clear and concise manner
Help other students with SQL
Help other students with SQL to reinforce your own understanding
Browse courses on SQL
Show steps
  • Join a study group or online forum
  • Answer questions and provide guidance to other students

Career center

Learners who complete Data Engineering will develop knowledge and skills that may be useful to these careers:
Data Engineer
Data Engineers build and maintain data pipelines. They ensure that data is collected, stored, and processed correctly. They also develop tools and processes for data analysis and visualization. This course would be a perfect fit for Data Engineers because it covers all the essential topics needed to succeed in this role, including data acquisition, storage, analysis, and visualization. The course also provides hands-on experience with data engineering tools and technologies.
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. They use data to train models that can predict outcomes or make decisions. This course would be helpful for Machine Learning Engineers because it provides a strong foundation in data engineering principles and practices. The course covers topics such as data collection, data analysis, and data visualization, which are all essential for Machine Learning Engineers to know.
Software Engineer
Software Engineers design, develop, and test software. They write code, debug systems, and create complex algorithms. This course would be helpful for Software Engineers because it teaches the basics of data engineering, which is a key skill for developing data-driven software applications. This course covers data acquisition, storage, and analysis, which are all essential topics for Software Engineers to understand.
Software Developer
Software Developers design, develop, and test software applications. They write code, debug systems, and create complex algorithms. This course would be helpful for Software Developers because it provides a solid foundation in data engineering principles and practices. The course covers topics such as data storage, data processing, and data visualization, which are all essential for Software Developers to know.
Data Governance Specialist
Data Governance Specialists develop and implement policies and procedures for managing data. They ensure that data is accurate, consistent, and accessible. This course would be helpful for Data Governance Specialists because it provides a solid foundation in data engineering principles and practices. The course covers topics such as data quality, data security, and data privacy, which are all essential for Data Governance Specialists to know.
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. They use statistical and machine learning techniques to identify trends, patterns, and insights in data. This course would be helpful for Data Analysts because it provides a strong foundation in data engineering, which is essential for managing and analyzing large datasets. The course also covers data visualization techniques and how to communicate insights to stakeholders.
Data Scientist
Data Scientists use data to build predictive models and solve business problems. They have a strong foundation in statistics, machine learning, and data engineering. This course would be helpful for Data Scientists because it provides a solid foundation in data engineering, which is essential for building and deploying data-driven models. The course also covers topics such as data visualization and communicating insights to stakeholders.
Cloud Engineer
Cloud Engineers design, build, and maintain cloud computing systems. They ensure that cloud systems are scalable, reliable, and secure. This course would be helpful for Cloud Engineers because it provides a solid foundation in data engineering principles and practices. The course covers topics such as data storage, data processing, and data security, which are all essential for Cloud Engineers to know.
Data Architect
Data Architects design and build data warehouses and data lakes. They ensure that data is stored and organized in a way that meets the needs of the business. This course would be helpful for Data Architects because it provides a deep understanding of data engineering principles and practices. The course covers topics such as data modeling, data storage, and data security, which are all essential for Data Architects to know.
Information Security Analyst
Information Security Analysts protect computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. This course would be helpful for Information Security Analysts because it provides a solid foundation in data engineering principles and practices. The course covers topics such as data security, data privacy, and data forensics, which are all essential for Information Security Analysts to know.
Database Administrator
Database Administrators manage and maintain databases. They ensure that data is stored securely and efficiently. They also optimize database performance and troubleshoot problems. This course would be helpful for Database Administrators because it provides a deep understanding of data engineering principles and practices. The course covers topics such as data modeling, data storage, and data security, which are all essential for Database Administrators to know.
Business Analyst
Business Analysts analyze business processes and identify opportunities for improvement. They use data to develop recommendations for new products, services, or processes. This course would be helpful for Business Analysts because it provides a strong foundation in data engineering principles and practices. The course covers topics such as data collection, data analysis, and data visualization, which are all essential for Business Analysts to know.
Network Engineer
Network Engineers design, build, and maintain computer networks. They ensure that networks are reliable, secure, and scalable. This course would be helpful for Network Engineers because it provides a solid foundation in data engineering principles and practices. The course covers topics such as data transmission, data security, and network troubleshooting, which are all essential for Network Engineers to know.
Project Manager
Project Managers plan, execute, and close projects. They manage resources, timelines, and budgets. They also communicate with stakeholders and resolve issues. This course would be helpful for Project Managers because it provides a solid foundation in data engineering principles and practices. The course covers topics such as data management, data analysis, and data visualization, which are all essential for Project Managers to know.
Product Manager
Product Managers manage the development and launch of new products. They work with engineers, designers, and marketers to ensure that products meet customer needs. This course would be helpful for Product Managers because it provides a solid foundation in data engineering principles and practices. The course covers topics such as data collection, data analysis, and data visualization, which are all essential for Product Managers to know.

Reading list

We've selected 11 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 Data Engineering.
Provides a comprehensive overview of the principles and techniques behind designing and building data-intensive applications.
Provides a comprehensive overview of data engineering with Apache Spark and useful reference tool for those who want to learn more about the subject.
Serves as a thorough guide to dimensional modeling, providing a strong foundation for understanding the database structures covered in the course.
Provides a comprehensive overview of data engineering with Haskell and useful reference tool for those who want to learn more about the subject.
Provides a comprehensive overview of data engineering with F# and useful reference tool for those who want to learn more about the subject.
Provides a comprehensive overview of data engineering with Google BigQuery and useful reference tool for those who want to learn more about the subject.
Provides a comprehensive overview of data engineering with R and useful reference tool for those who want to learn more about the subject.
Provides a comprehensive overview of data engineering with Go and useful reference tool for those who want to learn more about the subject.

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