目錄

---

1. Exploratory Data Analysis in SQL
2. Data-Driven Decision Making in SQL
3. Applying SQL to Real-World Problems
4. Analyzing Business Data in SQL
5. Reporting in SQL

Exploratory Data Analysis in SQL

---

What’s in the database?

Code	Note
NULL	missing
NULL, IS NOT NULL	don’t use = NULL
count(*)	number of rows
count(column_name)	number of non-NULL values
count(DISTINCT column_name)	number of different non-NULL values
SELECT DISTINCT column_name ...	distinct values, including NULL

SELECT *
    FROM company;
LIMIT 5

SELECT count(*) - count(ticker) AS missing
  FROM fortune500;

SELECT company.name 
-- Table(s) to select from
  FROM company 
       INNER JOIN fortune500 
       ON company.ticker=fortune500.ticker;

Summarizing and aggregating numeric data

Exploring categorical data and unstructured text

Working with dates and timestamps

Data-Driven Decision Making in SQL

---

Introduction to business intelligence for a online movie rental database

Decision Making with simple SQL queries

Data Driven Decision Making with advanced SQL queries

Data Driven Decision Making with OLAP SQL queries

Applying SQL to Real-World Problems

---

Use Real-World SQL

Find Your Data

Manage Your Data

Best Practices for Writing SQL

Analyzing Business Data in SQL

---

Revenue, Cost, and Profit

User-Centric KPIs

ARPU, Histograms, and Percentiles

Generating an Executive Report

Reporting in SQL

---

Exploring the Olympics Dataset

Creating Reports

Cleaning & Validation

Complex Calculations