Project

Recycling Organization

Medium

12 completions

~ 8 hours

4.3

Discover the Recycle Organization Database project and explore advanced topics like statistical functions such as percentile_cont, various types of JOINs, multiple subqueries, and different aggregate functions. Dive into GROUP BY, set operations, and conditional functions to grasp the full extent of SQL's capabilities. The project is dedicated to the learners who completed the SQL for Data Analysis course.

Provided by

JetBrains Academy

About

Welcome to the Recycling Organization Database, where you'll examine as a novice data analyst income and outcome data from two accounting companies hired by the recycling organization to manage their data. Your job is to compare and analyze the financial records of these companies. Discover insights to guide decision-making and strategic planning, aiming to improve financial transaction efficiency for the recycling organization Join us as we dive into financial data to optimize the recycling organization's income.

Training project

This project allows you to practice and strengthen your coding skills, helping you get ready for more advanced tasks ahead.

What you'll learn

Once you choose a project, we'll provide you with a study plan that includes all the necessary topics from your course to get it built. Here’s what awaits you:

Retrieve statistical data such as mean, median, total range, interquartile range, standard deviation, and variance for the recorded income data of both accounting companies.

Merge data from both accounting companies's Income tables to create a comprehensive overview of income transactions.

Compute the total income, total outcome, and net income for each pick-up point separately for both accounting companies.

Compare the outcome money of both accounting companies, identifying instances where one company's data records of outcome money exceeds or falls short of the other.

Aggregate the income and outcome data from both accounting companies into a unified dataset.

Reviews

lionel davy Kouemeni Tchako

6 months ago

5.0

Advanced Joins: Emulating FULL OUTER JOIN in MySQL using UNION ALL and Anti-Joins (LEFT JOIN with IS NULL filtering). Common Table Expressions (CTEs): Breaking down complex, multi-step financial aggregations into readable, modular WITH blocks. Window Functions: Using NTILE() for statistical quarti ...

Mauro Gonçalves

1 year ago

4.7

I Learned How to calculate various statistics (mean, range, standard deviation, variance) using SQL aggregate functions.

Ayush Nagar

2 years ago

5.0

I learned a lot about writing advanced queries, subqueries, types of JOINs, grouping, WITH, CASE, COALESCE statements and much more in MySQL by completing this real-world project.

4.3

Learners who completed this project within the Databases with SQL and Python course rated it as follows:

Usefulness

4.5

Fun

4.3

Clarity

4.1