3.4. Live vs Warehoused Connectors

3.4. Live vs Warehoused Data Connectors in Looker Studio

In this lesson we will discuss the pros and cons of using a Live connector (such as Google connectors and Supermetrics) when it comes to data freshness, price, loading speed, reliability, and data transformation or modeling capability.

Live Connectors

Live connectors are all about real-time data. When a Looker Studio report loads, the data connector receives the settings from the data source, connects to the dataset through an API, and extracts data to provide it to Looker Studio. This process happens live, which means that data is fresh and up-to-date.

Some pros of live connectors are:

They're cheaper, as they're just lines of code that run when needed.
They provide real-time data, so you always have the freshest information.

However, live connectors have some cons as well:

They're slower and less reliable because they depend on the dataset's API being available and quick.
They usually don't involve data modeling, as it takes time and isn't very feasible.

Most Google connectors are live connectors.

Warehoused Connectors

Warehoused connectors work differently. The creator of the connector sets up a data warehouse that extracts, transforms, and stores data on a schedule. This means that Looker Studio connects to a snapshot of the data in the data warehouse rather than directly to the dataset.

Some benefits of warehoused connectors are:

They're faster and more reliable, as they depend on the data warehouse's speed and availability.
They allow for data modeling, as data can be processed and transformed within the data warehouse.

However, there are drawbacks to warehoused connectors too:

They're more expensive, as maintaining a data warehouse requires additional infrastructure.
They're not real-time, as Looker Studio connects to snapshots of data rather than live data.

Examples of warehoused connector providers include Supermetrics, Power My Analytics, and Dataddo.

You can also create your own warehoused data connector using Google Sheets or BigQuery. Extract data to Google Sheets or BigQuery, transform and model it, and then connect it to Looker Studio for visualization. This approach can help create responsive, quick-to-load reports without the need for real-time data.

Understanding data connectors is essential when working with Looker Studio. They are the key to connecting and visualizing data from various sources. By exploring the different types of connectors and their capabilities, you'll be better equipped to create dynamic and informative reports in Looker Studio.