Google Data Studio course at CXL Institute

Google’s version of Tableau

Photo by Leon on Unsplash

Today I’m doing a review of Google Data Studio course on CXL Institute. It’s divided in 12 chapter and taught by Michele KISS, a well-known Digital analyst.

GDS is a web based free data visualization product connected to a lot of different data sources. It natively connects to a lot of Google data sources, but it also connects to other data sources.

If you are a GA user, you can build your reports with it without the need of GDS. But if you want advanced chart and a way put data from different data source on the same report, you must use GDS.

With this course, you will Learn to create more insightful reports and save time in the process with Data Studio.

COURSE SUMMARY

  • Getting started
  • Building charts
  • Using color
  • Dates
  • Filters, controls and segments
  • Calculated fields
  • Blends
  • Changing data sources
  • Sharing and access
  • Other useful features
  • Sampling
  • Cool uses of data studio

Before going to understand all the feature of Data studio, the teacher gives us a live look at the UI and see some of the features that we will find when first log in.

Inside DS there are native connectors for all of the popular Google products: Google Analytics, BigQuerry, Google Ads… There are also Partners connectors (Adobe Analytics…)

For Google Analytics data you will feel like a plug and play system: Google Analytics metrics are already setup with the appropriate aggregation and dimensions have already been set up as the appropriate type.

When creating Data source, Fields, Blend or anything else, make sure you give appropriate name to be able to automatically grasp what it’s about.

If you are serious about analytics, you want the Data-Pixel ratio so that we are using those pixels exclusively to display data. Making your reports and your visualizations as clean and concise as they can be.

BUILDING CHARTS

In this chapter you will learn how you can use different visualizations to convey different messages, how different chart types might work together to paint a really complete picture of your data, and how we can customize them to ensure that they’re communicating our data well.

This are the Data Visualizations available in DS:

  • Tables
  • Scorecards
  • Line charts
  • Bar, column and area charts
  • Pie and donut charts
  • Maps
  • Scatter plots
  • Pivot tables
  • Bullet
  • Tree maps

USING COLOR

In this chapter you will learn how you can intelligently use color in your reports and visualizations to help people to understand your data better.

DATES

In this chapter you will learn how dates need to be formatted, how you can customize date ranges for what you are reporting on, and also, how to deal with some common problems that can arise when you are using dates.

Date is a type within Data Studio and you want to make sure that your date field is actually set as that appropriate type.

FILTERS, CONTROLS AND SEGMENTS

Here you will learn how you, as the creators and the editors of reports, can filter Data Studio charts and tables, but also how you can create a way for your end users to do some filtering themselves and to customize the data that they are looking at and explore it within kind of a safe realm.

CALCULATED FIELDS

You are going to explore the power that you can get from calculated fields, to create customized metrics for what matters for your business. To create calculated dimensions that are going to help you to more concisely and cleanly explain your data, roll it up in ways that are going to help your end users

BLENDS (Also know as JOIN outside of Data Studio)

You’ll learn which type of “join” Data Studio uses, and how you can use it to combine multiple data sets. Blends are always a left join

CHANGING DATA SOURCES

If for some reason you have to change the backend data that one of your data sources is referring to. You could, of course, just create a new data source from scratch, and then you can go and link all your charts to it. The problem with doing that is that if you have created calculated metrics or calculated dimensions, you have to recreate all of those.

There’s no such as, currently, like an API, where I could just feed in all of the calculations and upload a hundred calculations at one time. What you want to do, is copy your data source, edit the connection, and change it behind the scenes, which is going to preserve all of the calculated fields that you have created.

SHARING AND ACCESS

You can share access with your data sources and your reports so that others can either view or edit them. If you’ve used Google Drive permissions for other kinds of documents it’ll seem pretty familiar, where you can set things so that they’re viewable to whoever is in your organization, if you happen to be a G Suite customer, or you can share specific links or just share with specific individuals. When you are creating a data source, you can configure it so that it either uses the owner’s credentials (anybody who looks at a report based on that data source is seeing data that I have access to) or the viewer’s credentials (the actual person who views the report needs access to). Sharing a report will allow users to edit the report. So they can use all of the existing fields in the data set. They can build new charts, they can delete pages out of your report. They can change anything in the report. But if you want them to be able to create new fields, or edit calculated fields that you already have in there, you have to make sure you specifically share edit access to the data source.

Data Studio doesn’t allow you to transfer the ownership of a report to somebody who is not in your org.

SAMPLING

This is only relative to GA as DS sample in the same conditions as GA. Sampling takes place in Google analytics if you run a custom query and you have more than a certain amount of traffic.

After this course you have to experiment a lot to be able to call yourself DS expert.