9.1. Introduction to Data Blending in Looker Studio
Data blending is a powerful technique that helps you merge and combine data from multiple sources into a single, unified dataset. In this lesson, we'll explore the foundations of data blending and why it matters for your Looker Studio projects.
Why Data Blending Matters
Understanding the "why" behind data blending can help you appreciate its potential for your data modeling projects. Let's dive into some use cases to see the different end results you can achieve with data blending:
1. Combine Fields from Different Data Sources
One of the primary benefits of data blending is the ability to combine fields from different data sources on a single chart. For instance, you might want to show costs from Facebook Ads, Google Ads, and Microsoft Ads on one chart to get a comprehensive view of your marketing spend across platforms.
2. Aggregate Data from the Same Marketing Tool
You can also use data blending to aggregate data from the same marketing tool but for different accounts. For example, you might want to see a roll-up chart displaying summarized data from multiple Google Ads accounts for all your clients.
3. De-Aggregate and Re-Aggregate Data
Data blending allows you to de-aggregate and re-aggregate data, which is often the only way to achieve the desired results. We'll see an example of this later in the session.
4. Blend Data for Calculated Fields
Data blending enables you to create calculated fields using data from different sources. For example, you might want to calculate the conversion rate using metrics from multiple data sources.
5. Enrich and Widen Data
Data enrichment and widening are useful techniques for adding more context to your dataset. For instance, you can enrich your data by looking up the profit margin for each SKU on an e-commerce site or by adding population data for a city. In both cases, you're "widening" your dataset by adding more columns of information.