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Data Wrangling, Analysis and AB Testing with SQL

This course allows you to apply the SQL skills taught in “SQL for Data Science” to four increasingly complex and authentic data science inquiry case studies. We'll learn how to convert timestamps of all types to common formats and perform date/time calculations. We'll select and perform the optimal JOIN for a data science inquiry and clean data within an analysis dataset by deduping, running quality checks, backfilling, and handling nulls. We'll learn how to segment and analyze data per segment using windowing functions and use case statements to execute conditional logic to address a data science inquiry. We'll also describe how to convert a query into a scheduled job and how to insert data into a date partition. Finally, given a predictive analysis need, we'll engineer a feature from raw data using the tools and skills we've built over the course. The real-world application of these skills will give you the framework for performing the analysis of an AB test.

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Syllabus

Data of Unknown Quality

In this module, you will be able to create trustworthy analysis from a new set of data. You will be able to coalesce some nulls and identify unreliable data and discover reasons why data might be missing. You will also be able to answer ambiguous questions by defining new metrics.

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Provides you with practical knowledge of SQL to address data science questions using case studies

Helps you develop proficiency in using SQL for data analysis and problem-solving

Suitable for learners with prior experience in SQL and data analysis

Focuses on practical application of SQL skills, which can be valuable for career advancement

Covers essential concepts such as data cleaning, data manipulation, and analysis

Provides a strong foundation for further exploration in data science

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Reviews summary

Applying sql for data analysis and ab testing

According to learners, this course is a highly practical application of SQL skills to real-world data analysis tasks, particularly focusing on data wrangling, cleaning, and the methodology of AB testing. Students appreciate the case studies which provide hands-on experience, finding the content relevant for careers in data science and analysis. Many feel it effectively bridges the gap between theoretical SQL knowledge and its use in solving business problems. While generally positive, some learners suggest having a solid foundation in SQL is beneficial before starting, and a few found certain aspects challenging or desired more depth in specific areas.

Can be challenging but rewarding.

"It was challenging at times, especially connecting all the pieces in the case studies, but ultimately very rewarding."

"The exercises pushed me to think critically about how to structure queries for specific analytical needs."

"I found the progression of case studies increasingly complex, which was a good test of skills."

"Be prepared to spend time working through the problems; they are not trivial."

Better suited for those with prior SQL experience.

"This course is definitely not for absolute beginners in SQL. You need a solid foundation coming in."

"I struggled a bit because my SQL background wasn't as strong as needed. Recommend taking the prerequisite course first."

"While it reviews some concepts, this course focuses on *applying* SQL, not teaching it from scratch."

"I recommend having a good grasp of joins and window functions before starting this."

Good coverage of cleaning and preparing data.

"The modules on data wrangling and cleaning were very thorough and directly applicable to messy real-world data."

"I learned valuable techniques for handling nulls, duplicates, and ensuring data quality for analysis."

"Understanding how to prepare data of unknown quality was a key takeaway for me."

"The sections on identifying unreliable data and cleaning datasets were highly beneficial."

Case studies, especially AB testing, are highlight.

"The case studies were highly relevant and engaging, providing a clear context for applying the SQL techniques learned."

"The AB testing case study was particularly useful and well-structured, giving me a solid framework for performing this common analysis."

"I really enjoyed working through the different data inquiry scenarios; they felt very authentic."

"Applying my skills in the AB testing module was the strongest part of the course for me."

Provides valuable real-world application of SQL.

"This course is a great way to learn how to apply the SQL concepts in real world business problems, like AB testing analysis."

"I found this course extremely valuable as it shifted the focus from learning SQL commands to using SQL to solve actual business problems."

"The hands-on application of SQL in realistic case studies really helped solidify my understanding and prepare me for practical work."

"I learned how to use practical tools and strategies that I could apply immediately to my work as a data analyst."

Some areas could benefit from more detail.

"While the overview is good, I wished some topics, like the statistical aspects of AB testing, went into more depth."

"Could use more in-depth coverage on complex window functions or specific optimization techniques."

"I felt some explanations were a bit too brief and required external resources for full understanding."

"The course provides a good foundation, but deeper dives into certain analytical techniques would be great."

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 Wrangling, Analysis and AB Testing with SQL with these activities:

Organize and Review Course Materials

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This activity helps you organize and consolidate your learning materials, making them easier to access and review, which can improve your retention and understanding.

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Gather all course materials, including lecture notes, assignments, quizzes, and exams.
Organize the materials into a logical structure.
Review the materials regularly.

Execute SQL Queries on Sample Datasets

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This activity allows you to practice executing SQL queries on sample datasets, which will reinforce your understanding of the SQL concepts covered in the course and help you develop proficiency in writing efficient and accurate SQL queries.

Browse courses on SQL Joins

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Obtain sample datasets from the course materials or other sources.
Write SQL queries to perform data cleaning, transformations, and aggregations on the sample datasets.
Execute the queries and verify the results against expected outputs.
Identify and correct any errors or inefficiencies in your queries.

Create a Visual Guide to SQL Concepts

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This activity encourages you to synthesize your understanding of SQL concepts and express them in a visual format, which can strengthen your comprehension and make it easier to share your knowledge with others.

Browse courses on Data Visualization

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Identify the key SQL concepts you want to visualize.
Choose a visual format, such as a flowchart, diagram, or infographic.
Create the visual guide, using clear and concise language and visuals.
Share your visual guide with others for feedback and discussion.

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Career center

Learners who complete Data Wrangling, Analysis and AB Testing with SQL will develop knowledge and skills that may be useful to these careers:

Data Analyst

A Data Analyst takes large amounts of raw data and turns it into actionable insights. Using SQL, a Data Analyst would be able to help a business improve through data-driven decision making. This course can help students gain the foundational skills necessary for Data Analysts to perform in their role. Particularly relevant to this role, the course covers topics such as data cleansing, data analysis, and A/B testing.

See salaries and explore the career path for Data Analyst

Data Scientist

A Data Scientist uses mathematics, statistics, and computing to solve problems. They use SQL to clean, transform, and analyze data in various formats. This course can help learners develop the necessary skills to work in this role by teaching them how to wrangle, analyze, and test data using SQL, which will be useful for performing data-driven analyses and extracting insights from data.

See salaries and explore the career path for Data Scientist

Business Analyst

A Business Analyst uses data analysis to identify and solve business problems. This course can help learners develop the SQL skills necessary for Business Analysts to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to use SQL to analyze data, make informed decisions, and improve business outcomes.

See salaries and explore the career path for Business Analyst

Data Engineer

A Data Engineer designs, builds, and maintains systems to manage and process data. This course can help learners develop the foundational skills necessary for Data Engineers to perform their role, such as data cleansing, data analysis, and A/B testing. By taking this course, learners can gain the skills to build scalable and reliable data pipelines, enabling them to support data-driven decision-making within an organization.

See salaries and explore the career path for Data Engineer

Statistician

A Statistician collects, analyzes, and interprets data to help organizations make informed decisions. This course can help learners develop the SQL skills that Statisticians need to perform their jobs, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to analyze and interpret data, draw conclusions, and make predictions.

See salaries and explore the career path for Statistician

Quantitative Analyst

A Quantitative Analyst uses mathematical and statistical models to analyze and predict financial data. This course can help learners develop the SQL skills necessary for Quantitative Analysts to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to analyze and interpret financial data, develop trading strategies, and make investment decisions.

See salaries and explore the career path for Quantitative Analyst

Machine Learning Engineer

A Machine Learning Engineer designs, builds, and deploys machine learning models. This course can help learners develop the SQL skills necessary for Machine Learning Engineers to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to prepare data for machine learning models, evaluate model performance, and deploy models into production.

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Data Science Manager

A Data Science Manager leads and manages data science teams. This course can help learners develop the SQL skills necessary for Data Science Managers to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to manage data science projects, communicate data analysis results, and lead teams of data scientists.

See salaries and explore the career path for Data Science Manager

Product Manager

A Product Manager is responsible for the development and launch of a product. This course can help learners develop the SQL skills necessary for Product Managers to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to analyze user data, identify product requirements, and make data-driven decisions.

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User Experience Researcher

A User Experience Researcher studies how users interact with products and services. This course can help learners develop the SQL skills necessary for User Experience Researchers to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to collect and analyze user data, design user experiences, and evaluate the effectiveness of user interfaces.

See salaries and explore the career path for User Experience Researcher

Data Visualization Specialist

A Data Visualization Specialist creates visual representations of data. This course can help learners develop the SQL skills necessary for Data Visualization Specialists to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to create clear and concise data visualizations that communicate insights effectively.

See salaries and explore the career path for Data Visualization Specialist

Database Administrator

A Database Administrator is responsible for the maintenance and performance of databases. This course can help learners develop the SQL skills necessary for Database Administrators to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to design and implement database systems, optimize database performance, and troubleshoot database issues.

See salaries and explore the career path for Database Administrator

Cloud Data Engineer

A Cloud Data Engineer designs, builds, and manages data pipelines in the cloud. This course can help learners develop the SQL skills necessary for Cloud Data Engineers to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to build and maintain scalable and reliable data pipelines in the cloud.

See salaries and explore the career path for Cloud Data Engineer

Data Architect

A Data Architect designs and implements data management solutions. This course can help learners develop the SQL skills necessary for Data Architects to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to design and implement data architectures, manage data quality, and ensure data security.

See salaries and explore the career path for Data Architect

Chief Data Officer

A Chief Data Officer is responsible for the overall data strategy and governance of an organization. This course may be useful for learners who aspire to become Chief Data Officers, as it can help them develop the SQL skills necessary to perform their daily tasks, such as data cleaning, data analysis, and A/B testing. By taking this course, learners can gain the skills to lead data initiatives, manage data resources, and ensure data compliance.

See salaries and explore the career path for Chief Data Officer

Reading list

We've selected 12 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 Wrangling, Analysis and AB Testing with SQL.

SQL Queries for Mere Mortals

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This commonly used introductory textbook for SQL. It explains the syntax and structure of SQL in a clear and concise way, making it a good resource for beginners.

Data Wrangling, Analysis and AB Testing with SQL

Here's a deal for you

What's inside

Syllabus

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Reviews summary

Applying sql for data analysis and ab testing

Activities

Career center

Reading list

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