Data preparation
To derive meaningful insights from these three different datasets, proper data preparation is crucial. In this section, we will explore a few ways to prepare and harmonize data from Google Analytics, Google Ads, and e-commerce sales sources for effective analysis and reporting. We will use the data definition language (DDL) and data manipulation language (DML). We introduced DDL and DML in Chapter 4, Loading and Transforming Data, and explored these concepts further in Chapter 8, An Overview of Data Preparation Tools.
To prepare our datasets for insights and exploration, we will standardize date formats across our data sources. Let’s get started!
Standardizing date formats
Across our three data sources, there are three different date columns. This is an opportunity for us to standardize, making querying and joining data easier later. In the following table, you can see the three columns and the unique way they are named, as well as their data types...
