Data exploration and analysis

Let’s do some exploration and analysis of our customer support datasets. The following queries will allow us to unlock some insights and better understand what is happening with customer support.

Count of ticket_type across both datasets

This query uses the UNION DISTINCT function to list all of the category and ticket_type records across both of our customer support datasets. This data could be helpful to better understand the most common and least common ticket types for improvements and prioritization:

#ticket types and their counts across both datasets
SELECT category, count(category) as count
FROM `ch13.bitextcustomersupport`
GROUP BY category
UNION DISTINCT
SELECT ticket_type, count(ticket_type) as count
FROM `ch13.customersupport`
GROUP by ticket_type
ORDER BY count desc

https://tinyurl.com/5brcxzy3

The following query results show the top ticket types across both support data sources.

Figure 13.11...