Data connectors in Google Data Studio
The provided data sets in the Data Viz Starter Pack are pulled into Google Data Studio via two connectors: Google Sheets and Google Cloud SQL. Many educators today manage their school or class data via Google Sheets so it felt right to meet them where they are. Google Sheets is a quick and easy way to store tabular data and make changes to it as needed. Google Data Studio can ingest that data so it may be used to build data dashboards. An important thing to note is that Data Studio never imports the data, it keeps it in the Google Sheet. This means that as the Sheet changes, the report changes.
The Starter Pack can also store your data sets in Google Cloud SQL, a fully-managed database service. The only reason we do this is for performance. From our end, we see reports load faster when they use a Cloud SQL backend. This would typically add a layer of complexity due to SQL requiring you to define a schema for each table in the database beforehand. However, we handle this piece for you. The first time the Starter Pack pushes a data set to Cloud SQL, it creates the table with the proper schema attached to it.
Connecting your data
Do you manage some of your data in Google Sheets? A few quick steps and that data can be in Google Data Studio alongside the data available to you via the Starter Pack. A Data Studio report gives you the ability to include as many data sources as you’d like. You can have a few charts that utilize a data set from the Starter Pack right next to a table or chart that is linked to one of your Google Sheets. For example, imagine bringing in a reading intervention tracker and layering on attendance information.
To help combine (or blend) data together, data sets in the Starter Pack use a few unique identifiers that are already familiar to you: student ids, user ids, and course ids to name a few. There is a feature in Data Studio where you can link two data sources together via a key such as a student’s id number. This is called blending data. We have designed our data sets with this feature in mind.
For example, there is a data set, Course Enrollments, that will give you current students and the courses they are enrolled in. This data set has a column for the student id + columns that list course information, but does not give you student fields such as their last or first name. In Data Studio you would join this data set with the Student Demographics & Enrollment data set to bring in this data.
All Starter Pack schools use data sets of the same schema and we document it all on one Google Sheet. With data blending, you can really start to see the importance of using unique identifiers in your data sets.
There are a few other connectors that you may find interesting. You can upload a CSV file directly, connect to a SQL database that is not Google Cloud SQL, or use a few that have been created by AmplifiedIT to bring in data on your school’s Chromebook utilization and device versions to ensure your Chromebooks are up to date and being used.
In a future post we will dig into what’s inside each data set provided by the Starter Pack.