Gain insights into advanced SQL data analysis techniques. Explore producing descriptive statistics, handling missing data, and analyzing time series. Discover aggregating results and preparing data for analysis.

SQL databases have been around since the 1970s. Some of the smartest people in the world worked on making it easy to slice, dice, fetch and manipulate data quickly and efficiently. SQL databases have come such a long way that many developers and data scientists have lost track of what they can do with plain SQL.

In this course, you will learn advanced concepts and techniques for analyzing data using SQL. You will obtain hands-on experience in producing descriptive statistics, breaking a large query into multiple steps and samples, and cleaning and preparing data for analysis. You will learn how to produce aggregate results and subtotals, analyze a time series using cumulative and window frames, how to handle and fill missing data, and how to produce buckets and histograms.

After completing this course, you will be able to gain actionable insight from your data using nothing but SQL!

Practical Data Analysis with SQL

# Overview


The `PARTITION` clause in an aggregate expression can calculate the difference between the temperature on each day and the hottest day ever in the same city:

SELECT 
  *,
  temperature - MAX(temperature) OVER (PARTITION BY city) AS diff_from_hottest
FROM 
  temperatures;

# Order of rows in a partition

To compare each temperature to the maximum temperature in the same city before that date, we need to add another element to our group. So far, we used the `PARTITION` clause to tell the databases how to group the data. Now, we want to provide order as well:

SELECT 
  *,
  MAX(temperature) OVER (
    PARTITION BY city ORDER BY day
  ) AS hottest_day_so_far
FROM 
  temperatures
ORDER BY
  city,
  day;

Learn how to calculate aggregate expression over a sliding window.

Introduction

Basic SQL for Data Analysis

Descriptive Statistics

Grouping and Subtotals

Running and Cumulative Aggregation

Interpolation

Binning

Conclusion

Window Frames

Overview

Order of rows in a partition