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DataCamp

Time Series Analysis in PostgreSQL

via DataCamp

Overview

Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.

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 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.

Syllabus

  • 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!
  • 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.
  • 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.
  • 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.

Taught by

Jasmin Ludolf

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