Google Data Studio

Introduction

Google Data Studio is a free tool that turns your data into informative, easy to read, easy to share, and fully customizable dashboards and reports. 

DataSet can be used as one of these sources and you can monitor the health of your systems with your Event Data Cloud data from a beautiful Google Data Studio dashboard. 

Tutorial

In this tutorial, we will set up GDS efficiently and bring in PowerQuery data. We will also manipulate the data from a single PowerQuery to add multiple visualizations and perform derivative computations to create new metrics  

PreReqs

• Google Account and GDS
• DataSet account with access to a read API key

Adding DataSet Data Source

1. Open Google Data Studio
2. Create a Blank Report
   
3. Add Data to Report and search for DataSet
   
4. Select DataSet Region -
   If you login to DataSet on app.scalyr.com then you will use US Region else if you use eu.scalyr.com then you will use EU Region
5. Add DataSet Read API Key - found here
   
6. Enter a PowerQuery for your first visualization. 
   In this case, I am bringing as much data as possible per call. Here is an example of a summary of accesslog data.
   dataset == 'accesslog' |group count=count(), latency = mean(time), successes = count(status<400),errors = count(status>=400), mean = mean(time), median = p50(time), p95 = p95(time) by serverHost |sort -mean
   

Deriving Metrics

When you bring in data from Google Data Studio, best practices is to limit the amount of API calls to DataSet. GDS helps with this with the ability to derive metrics and other visualizations from the data you bring into GDS. Meaning we can import much of our data in a table and perform in-app computations. 

1. Add Metric
   
2. In this example, we can sum the count for all serverHosts to create count_of_all 
   
   
3. Here is an example of utilizing multiple metrics and visualizations to minimize API calls 
4.