SQL for Data Analytics

7. Analytics Using Complex Data Types

Learning Objectives

By the end of this chapter, you will be able to:

• Perform descriptive analytics on time series data using DATETIME
• Use geospatial data to identify relationships
• Use complex data types (arrays, JSON, and JSONB)
• Perform text analytics

This chapter covers how to make the most of your data by analyzing complex and alternative data types.

Introduction

In the previous chapter, we looked at how we can import and export data into other analytical tools in order to leverage analytical tools outside of our database. It is often easiest to analyze numbers, but in the real world, data is frequently found in other formats: words, locations, dates, and sometimes complex data structures. In ...