SQL for Data Analytics by Upom Malik

Author:Upom Malik
Language: eng
Format: epub
Publisher: Packt Publishing
Published: 2019-08-21T16:00:00+00:00

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 this chapter, we will look at these other formats, and see how we can use this data in our analysis.

First, we will look at two commonly found column types: datetime columns and latitude and longitude columns. These data types will give us a foundational understanding of how to understand our data from both a temporal and a geospatial perspective. Next, we will look at complex data types, such as arrays and JSON, and learn how to extract data points from these complex data types. These data structures are often used for alternative data, or log-level data, such as website logs. Finally, we will look at how we can extract meaning out of text in our database and use text data to extract insights.

By the end of the chapter, you will have broadened your analysis capabilities so that you can leverage just about any type of data available to you.

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.