Skip to content

8 Week SQL Challenge with outputs in Jupyter Notebook and executions using SQLite and Pandas

Notifications You must be signed in to change notification settings

20100215/8_Week_SQL_Challenge

Repository files navigation

8 Week SQL Challenge

8 Week SQL Challenge

A compilation of case study solutions with practical and complex SQL queries for data manipulation, analysis, and reporting covering the following domains of analytics: Health, marketing, people, finance, fast moving consumer goods, and digital marketing. This demonstrates my proficiency in writing SQL queries, solving problems, and obtaining key metrics in every challenge. Created by Data with Danny (Source: #8WeekSQLChallenge)

For starters: Read here on why SQL is an essential skill for all data-related roles such as data engineers and data analysts.

Skills: Data Preparation, Data Cleaning, Data Management, Data Analysis and Reporting

Tools: SQLite, Jupyter Notebook

Projects:

  1. Week 1: Danny's Diner - (Questions)
  2. Week 2: Pizza Runner - (Questions)
  3. Week 3: Foodie-Fi - (Questions)
  4. Week 4: Data Bank - (Questions)
  5. Week 5: Data Mart - (Questions)
  6. Week 6: CliqueBait (Posting soon)
  7. Week 7: Balanced Tree (Posting soon)
  8. Week 8: Fresh Segments (Posting soon)

Feel free to click the links above and explore the outputs, queries, and insights from each case study! :)

SQL Skills Gained:

  • Data cleaning & transformation
  • Aggregations
  • Joins
  • Common Table Expressions (CTEs)
  • Variables
  • Window functions
    • PARTITION BY, ORDER BY
    • Ranking (ROW_NUMBER, DENSE_RANK)
    • Analytics (LEAD, LAG)
    • Ranges of calculations (ROWS BETWEEN)
  • CASE WHEN statements
  • Subqueries
  • UNION, INTERSECT, EXCEPT
  • DATETIME functions (DATE_PART, DATE_TRUNC)
  • Data type conversion
  • TEXT functions, text and string manipulation

Note: Weeks 1-3 solutions are done using SQLite, while weeks 4-8 solutions are done using PostgreSQL.

Last updated July 18, 2024

About

8 Week SQL Challenge with outputs in Jupyter Notebook and executions using SQLite and Pandas

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published