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

SELECT
    role,
    department,
    COUNT(*) as employees
FROM
    emp
GROUP BY
    role,
    department;

## The `ROLLUP` query

If we want to include the number of employees in each department across all roles, we need the results at a higher level than the query currently provides. The query aggregates combinations of department and role, but we want aggregates at the role level alone. For example, to get the number of all the employees in the R&D department, we can sum the results of the rows in the output for the R&D department. This is often called “rolling up.”

To include the number of employees in each department across all roles, we can instruct the database to roll up the results of this field:


Learn how to include subtotals in aggregate queries.

Introduction

Basic SQL for Data Analysis

Descriptive Statistics

Grouping and Subtotals

Running and Cumulative Aggregation

Interpolation

Binning

Conclusion

Subtotals

Overview

The `ROLLUP` query

Subtotals

Overview

The ROLLUP query

The `ROLLUP` query