Build your ultimate AI agent
Course Description
This course teaches you how to leverage PostgreSQL to handle date and time data. You'll learn about functions and calls to help you parse through and manipulate this data, make calculations, and use window functions.
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.
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.
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
Curriculum
Course outline
1
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!
- Introduction to date and time data types50 XP
- PostgreSQL data types50 XP
- INSERT time INTO table100 XP
- Working with time zone information50 XP
- Find the time zones100 XP
- Convert to a different time zone100 XP
- Converting between date, time, and text50 XP
- Casting dates100 XP
- Converting dates100 XP
- Converting date and times100 XP
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.
S
Time Series Analysis in PostgreSQL
Course
Complete
