Course
Time Series Analysis in PostgreSQL
IntermediateSkill Level
Updated 11/2025SQLData Manipulation4 hr14 videos46 Exercises3,800 XP2,457Statement of Accomplishment
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Work with time series data
You’ll learn about various date and time data types and how to convert between them, manipulate their granularity, and perform calculations, including aggregations, partitioning, and running averages. These insights will help you add value to existing time series data.
Apply time series analysis to real-world data
You'll apply these techniques to real-world data to analyze temperatures, look at train schedules, and review how the popularity of news articles can change over time.
Prerequisites
Joining Data in SQL1
Introduction to Date and Time Data in PostgreSQL
In this chapter, you’ll be introduced to date and time data types. You’ll learn how to convert text and numeric data to date and time format—and how to convert the other way around too!
2
Working with Time Series
It’s time to get granular. In this chapter, you’ll learn how to set the granularity of your time series reports. You’ll then get to grips with adding, subtracting, and aggregating as you discover how to analyze time series data.
3
Using Window Functions to Analyze Time Series Data
In this chapter, you’ll work with window functions. You'll begin learning about partitions and partitioning and how they work with window functions. You'll be able to find the top items when ranking your data.
4
Calculating Running Totals and Moving Averages
In the final chapter, you’ll level up your skills by calculating the running total, running average, and even moving average to enhance your time series analysis.
Time Series Analysis in PostgreSQL
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FAQs
What PostgreSQL techniques for time series data will I learn?
You will learn date and time type conversions, time granularity control, date arithmetic, aggregation over time periods, window functions with partitioning, and moving averages.
What real-world datasets are used in the exercises?
You will analyze temperature data, train schedules, and news article popularity trends to practice time series analysis techniques in PostgreSQL.
Do I need prior experience with window functions?
No. The course teaches window functions and partitioning from scratch in Chapter 3, building up to running totals and moving averages in the final chapter.
Is this course specific to PostgreSQL or applicable to other SQL databases?
The course uses PostgreSQL-specific date and time functions, but the concepts of window functions, aggregation, and time series analysis transfer to most SQL databases.
What SQL knowledge do I need before starting?
You should have completed Introduction to SQL, Intermediate SQL, and Joining Data in SQL to have the foundational query skills this course builds on.
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