Data Wrangling, Analysis and AB Testing with SQL

Go to Course: https://www.coursera.org/learn/data-wrangling-analysis-abtesting

Introduction

### Course Review: Data Wrangling, Analysis and AB Testing with SQL If you're looking to sharpen your SQL skills while diving into real-world data science scenarios, the "Data Wrangling, Analysis and AB Testing with SQL" course on Coursera is a stellar option. This course, designed for those who have a foundational understanding of SQL, builds upon the skills acquired in the “SQL for Data Science” course, and promises an in-depth application of these skills through hands-on case studies. #### Overview The course is structured around four engaging and progressively challenging data science inquiry case studies that reflect a variety of data challenges and opportunities. It combines theoretical knowledge with practical exercises, allowing students to apply the concepts they learn directly to the data they analyze. Throughout the course, students will explore essential SQL operations such as converting timestamps, performing joins, cleaning datasets, and executing AB tests. The curriculum is well-thought-out, showcasing key aspects of data manipulation and analysis that every aspiring data scientist should master. #### Syllabus Breakdown 1. **Data of Unknown Quality** This introductory module sets the stage for the importance of data quality in analysis. You will learn how to coalesce null values and sift through unreliable data. The ability to articulate reasons why data may be missing is crucial in any data analysis situation, and this module does an excellent job of equipping learners with the necessary skills to handle such scenarios. 2. **Creating Clean Datasets** Here, you’ll get hands-on experience cleaning data. The course dives into various data types and introduces key concepts such as data warehouses versus production databases. By the end of this module, you will not only understand how to manipulate unfiltered data into reliable datasets but will also appreciate the importance of maintaining data integrity. 3. **SQL Problem Solving** This module tackles the essential skill of problem-solving through SQL. You’ll learn techniques for mapping joins and addressing a range of data-related questions. The focus is on developing strategies for pulling insights from data and effectively communicating results, which is vital for any data scientist. 4. **Case Study: AB Testing** This final module culminates in a practical application of your SQL skills through setting up a basic AB testing system. You’ll learn how to apply hypothesis testing, interpret results, and connect them to business metrics. This experience not only reinforces your SQL capabilities but also sets a solid foundation for understanding more advanced statistical analysis techniques in the future. #### Review and Recommendation The "Data Wrangling, Analysis and AB Testing with SQL" course is commendable for those aiming to deepen their understanding of data manipulation and analytics. The modular approach ensures that learners gradually build their skills and can appreciate each step's relevance. The hands-on case studies encourage active learning and real-world application, making complex concepts easier to grasp. I highly recommend this course for: - **Aspiring Data Scientists:** If you're looking to solidify your SQL skills in a way that applies directly to data science, this course is a perfect choice. - **Professionals in Analytics:** Those in marketing, business analysis, or related fields will find this course valuable for managing and interpreting data effectively. - **Lifelong Learners:** If you're simply looking to expand your skillset and enhance your resume with data analysis capabilities, this course is an excellent investment. In conclusion, whether you are aiming to pivot your career towards data science or enhance your current analytics skills, "Data Wrangling, Analysis and AB Testing with SQL" on Coursera offers a robust framework to achieve your goals. With its mix of theoretical knowledge and practical application, you will be well-equipped to handle the data challenges of today and tomorrow.

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.

In this module, you will be able to name the main the categories of data types. You will be able to explain how the unfiltered data can be manipulated into a table where you can conduct data analysis. You will be able to discuss why a data warehouse is separate from a production database, and you will be able to use the tools you learned to create your own trustworthy tables.

In this module, you will be able to map out your joins and be able to highlight the level of detail needed for different kinds of questions. You will be able to practice answering data questions, which should help you feel ready to get asked a whole slough of questions, vague questions, ambiguous questions, or even poorly worded questions. Finally, you will develop a strategy for answering all those questions using data.

In this module, you will be able to use your SQL skills to set up a basic AB testing system. You will be able to apply hypothesis testing to prove or disprove a hypothesis about how user behavior changed. You will be able to test and interpret the results using a metric or metrics that are tied directly to some business metrics. You will be able to test your SQL skills and give you the base experience you need to learn anything more complicated in terms of AB testing in the future.