Tai Chou-Kudu

#100DaysOfDataAnalytics #Excel #SQL #Tableau #PowerBI #DataAnalytics #DataVisualization #Databases #100DaysOfDataAnalyticsChallenge 100 days of Data Analytics inspired by @thenadcoder Day 1-8: Excel Day 9-60: SQL Day 61-100: Tableau/Power BI

If you're looking for a career coach, Isaac has sliding scale services and is an ex-Netflix and Goldman Sachs employee who currently does Analytics for Good in healthcare. He's been super helpful on my job search! If you arrange a call with him, tell him Tai sent you!

100 days of Data turned into 50! One of the most supportive things I've done lately is join a data fellowship where I've had the opportunity to use SQL and Python to advance progressive causes for organizations focuses on decriminalization efforts.

DAY 51: My Final SQL Project Exploring DVD Rental Business Trends github.com/tai-chou-kudu/…

DAY 50: Putting a SQL Final Project on Git Hub, tutorial youtube.com/watch?v=0N9xek…

DAY 49: Practicing SQL by going through this SQL Bolt sequence. Great resource for #SQLPractice, whether you're just beginning, or solidifying what you know like me. sqlbolt.com

DAY 48: Here is the solution to the #SQLPractice Problem from Day 40.

DAY 41: Write a query to list first_name and last_name of actors/actresses and the titles of films they have acted in. Include actors/actresses who have not acted in any film. Hints below

DAY 47: Here is the solution for #SQLPractice Problem on Day 40

DAY 40: Practice JOINs using the Sample DVD Rental set I told you how to set up earlier. TASK: Join the film to the film_actor table

I will post the answer for this soon!

I will post the answer for this soon!

DAY 46 #SQLPracticeProblem solution

DAY 46: GROUP BY/HAVING BY review Write a query to list all actors/ actresses who have appeared in more than 20 films? solution below

DAY 45: Stay tuned for DAY 40-41 solutions to #SQLPracticeProblems on #SQLJOINs Explore EXTRACT in the DVD rental sample dataset.

DAY 44: #ExtractFunction #SQLExtract Very helpful for working with timestamp data when you need to see a specific part of the date like month, day, year, or even minute. EXTRACT can be used in SELECT along with other columns. EXTRACT can be used with group by/order by

DAY 43: Stay tuned for DAY 40-41 solutions to #SQLPracticeProblems on #SQLJOINs Today, we'll continue the UNION lesson and learn about UNION ALL.

DAY 42: Stay tuned for solutions to DAY 40-41 of #SQLJOINPracticeProblems Today, we'll learn about #UNION.

1. which table of dvd rental contains actor first and last names? we'll need this table 2. which table of dvd rental contains titles of films? we will need this table too 3. what type of join will include all entries from the left table, even if the right one does not match?

hint: see what the primary key is for each table, and check what columns the tables have in common. This is an important first step.

JOINs can be tricky, so practice makes perfect.

DAY 39: Reviewing #SQLJOINs, back to the basics. The order of JOIN queries are important to remember! Do some practice on the dvdrental sample database (instructions on how to download are further down my page), and using the ER diagram if needed to determine where you can JOIN!