Google released their beautiful dashboard-building powerhouse, Data Studio, in Fall 2016.
We've been actively building dashboards with it ever since.
Ascending new heights. Stretching the limits of what's possible with Data Studio. You get the picture.
We've turned this tool inside out, and now are here to share everything we've learned.
During the course, you'll master how to build Data Studio reports.
All of these dashboards are based on raw data from Google Sheets, but the same methods could be used for any data source (Google Analytics, Youtube, a database, etc):
Your team will thank you, when they bask in the beauty and elegance of your next monthly update.
Walking through what we'll actually *do* here.
The course project is a Data Studio dashboard based on Twitter analytics data - which has been dropped into a handy Google Sheet for our analysis.
We'll use Data Studio to calculate new metrics, make sexy charts, and generally squeeze the lemon that is this Twitter data.
To get started, make a copy of the course Twitter data here:
Data Studio is somewhat temperamental - it requires your Sheets to be in a specific format to read them correctly.
Date columns in particular can be tricky, so you won't want to miss this lesson.
Every piece of data in Data Studio is a *Data Source*, which you need to connect before you can build any charts or tables with it.
This includes Google Analytics, Youtube, or any of the native sources that sync with Data Studio - but in this tutorial we'll focus on connecting a Google Sheet.
Fields in data studio are either dimensions or metrics.
Dimensions are text values like your City or State.
Metrics are number values like your Height.
If you've worked with Google Analytics data before, this will look familiar to you.
Getting your feet wet with building basic charts - feel for the first time the glorious bells and whistles of the Data Studio sidebar.
Being able to compare metrics between two date ranges is one of the most powerful features of Data Studio.
Learn how to put it into action.
Adding your first date filter to your report - the magic dropdown that makes your charts sing.
In many ways, calculated columns can *replace* work that you used to do in Google Sheets.
For more info on the formulas available in calculated columns, check out the attached Google docs.
Dive into the nuances of making your bar charts look oh so beautiful.
Scatterplot charts a bit more complex than bar charts - let's make sure you know how to wield them effectively.
When you start building multi-page dashboards, you'll want to add some titles, filters, charts or tables to *every* page, and some to just one page.
Classifying them as either Report or Page-Level allows you to do that.
Let's take your calculated column skills up a notch, by writing a function to count another column.
Building a 'count' column is the easiest way to get around Data Studio's pesky limitations on aggregating dimensions.
The CASE statement is the swiss army knife of custom functions in Data Studio.
You can use it to apply a time of day (morning / afternoon / night) based on an actual time (12:30pm), or to apply a type of tweet (retweet / primary tweet) based on tweet text.
It's a tough nut to crack, but opens up a world of possibilities in calculating your own metrics.
Often you'll want to strip out just one part of your dates - whether it's the day of the week, or month of the year.
Calculated columns allow you to seamlessly do that, without adding new data to your Sheet.
We already talked about adding filter control dropdown menus to your reports, but what about filtering behind the scenes?
Let's walk through how to add a custom filter to any chart or table.
With great power, comes great responsibility.
I'm currently the head of growth at Coach, a venture-backed education startup in New York City.
I publish everything I know about code-free automation on my blog, Coding Is For Losers, including a vault of Google Sheets templates.
I teach advanced Google Sheets, how to use Sheets add-ons like Blockspring, Supermetrics, and Zapier for data analysis, and SQL for beginners.