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

**(True or False)** The expression `COUNT(CASE WHEN role = 'Developer' THEN 1 ELSE NULL END)` is equivalent to `COUNT(*) FILTER (WHERE role = 'Developer')`. 

(True or False) The expression <code>COUNT(CASE WHEN role = 'Developer' THEN 1 ELSE NULL END)</code> is equivalent to <code>COUNT(*) FILTER (WHERE role = 'Developer')</code>.

**(True or False)** The expression `COUNT(CASE WHEN role = 'Developer' THEN 1 ELSE NULL END)` is equivalent to `SUM(CASE WHEN role = 'Developer' THEN 1 ELSE 0 END)`.

(True or False) The expression <code>COUNT(CASE WHEN role = 'Developer' THEN 1 ELSE NULL END)</code> is equivalent to <code>SUM(CASE WHEN role = 'Developer' THEN 1 ELSE 0 END)</code>.

**(True or False)** The `ROLLUP` and `CUBE` can be expressed using `GROUPING SETS`. 

(True or False) The <code>ROLLUP</code> and <code>CUBE</code> can be expressed using <code>GROUPING SETS</code>.

**(True or False)** To identify the rows with the subtotal results produced by `ROLLUP`, `CUBE`, or `GROUPING SETS`, we need to look for rows with missing values (`NULL`). 

(True or False) To identify the rows with the subtotal results produced by <code>ROLLUP</code>, <code>CUBE</code>, or <code>GROUPING SETS</code>, we need to look for rows with missing values (<code>NULL</code>).

Test your knowledge about the grouping and subtotals.

Test your knowledge about the grouping and subtotals.

Test yourself for grouping and subtotals in PostgreSQL.

Introduction

Basic SQL for Data Analysis

Descriptive Statistics

Grouping and Subtotals

Running and Cumulative Aggregation

Interpolation

Binning

Conclusion

Quiz: Grouping and Subtotals