What is Google Data Studio?
Data Studio is Google’s free data visualization and business intelligence reporting tool. It was launched in mid-2016 and came out of beta mode in October 2018.
It has a simple drag-and-drop interface, so you can easily add charts and build reports without needing any deep technical knowledge.
The premise is that you can connect all of your disparate business data sources and easily build beautiful, interactive dashboard reports to display that information, atop Google’s super-reliable, powerful, scalable architecture.
Why use it?
Ultimately, Data Studio is a tool you use as the final piece of your data analytics pipeline, to show your results visually and share insights and answers with others.
It’s free, which is a significant factor considering the steep cost of alternatives.
It’s simple and intuitive, so it doesn’t take long to get the hang of the basics. It’s very quick to create dashboards once you know the basics.
If you’re already using Google products in your analytics workflow, then it’s super easy to hook them up to Data Studio.
You get sharing and collaboration seamlessly built-in.
Of course, it has the reliability, scalability and support that only Google can provide.
It all starts with the data
The old adage “garbage in, garbage out” is as applicable to visual reporting as to any other sphere of computing.
Data Studio dashboards consist of two parts: the dashboard (obviously!) and the data source.
There are currently 18 Google Connectors which connect different Google platforms directly into Data Studio. One of these connectors is Google Sheets, which means that any data you can get into a Google Sheet is accessible for visualizing in Data Studio. In addition, you’ll see direct file uploads, popular SQL databases, BigQuery, Google Analytics, YouTube, Ads, Google Cloud services etc.
In addition, there are over a hundred partner connectors, which connect other third-party tools directly into Data Studio, although some of these connectors are paid services.
Data Studio works equally well for Google Sheets tables with 10 rows as it does with huge SQL or BigQuery datasets with millions of rows of data.
The first consideration, before you even open Google Data Studio, is to ensure that your data is ready, i.e. it’s accurate and complete.
Has it been de-duplicated? Have you checked that the numbers make sense? Do you have “impossible” dates way in the past or the future? Have you got spelling mistakes that will cause items to be wrongly categorized? Are you missing any data? Why is there no data for the month of May for example? (There could be a legitimate reason, but it’s important to know.)
It should be accurate and complete before you create and share a visual report which others may use to make decisions with.