DIGITAL ANALYTICS MINIDEGREE / CXL — BLOG 7
In the last blog post, I talked about the Microsoft Excel and Google Sheets for marketers, differences and similarities in detail. In this blog post, we will explore a great offering by Google which is Google Data Studio with the seventh part of CXL Digital Analytics Minidegree.
You can go to the CXL website from here.
What is Google Data Studio?
First of all, I will briefly talk about what Google Data Studio is and then I will begin to examine it in detail.
Data Studio is a free tool that turns your data into informative, easy to read, easy to share, and fully customizable dashboards and reports. Annotate and brand your reports with text and images. Apply styles and color themes that make your data stories works of data visualization art.
Terminology:
- Dimension: an attribute of a user (e.g.browser, gender etc.)
- Metric: measures characteristics of a dimension (e.g. sessions, new users, etc)
- Data Source: The place where your data comes from. (e.g. Google Analytics, spreadsheet, CRM, youtube etc.)
- Data Connectors: These are the connectors that are used to connect to the external source of data and bring the data into GDS.
Different Types of Dimensions:
- Number
- Text
- Date
- True/False
- Geo
- Currency
- URL
Different Types of Metrics:
- Number
- Percent
- 3. Duration
- 4. Currency
Benefits of Google Data Studio
1. Cloud-based and Completely Managed
Unlike most popular business intelligence tools like Power BI, Tableau, etc. Data Studio was designed from ground up as a cloud-based service. It is a completely managed service which means the user does not have to manage any kind of infrastructure or installation.
2. Tight Integration with Google’s Ecosystem
The biggest advantage offered by Data Studio is its ability to integrate seamlessly with Google applications like Google Analytics, Big Query, Google Sheets, etc. So if your ETL architecture is primarily built on top of Google applications, you will save a lot of time when integrating with Data Studio.
3. Easy to Use
Data Studio offers a very easy to use UI that will help anyone acquainted with Google products to start creating reports and dashboards within a few clicks. In that sense, it offers a very flat learning curve.
4. Access and Sharing Controls
Sharing reports and dashboards to other users and restricting access with a high degree of granularity is very easy in Data Studio.
5. Support for Live Connections
When compared to other BI tools like Power BI, Tableau, etc, Data Studio is designed on the premises of a live data connection. This means there is no elaborate logic or scheduled jobs required to manage the freshness of data. Anytime a report or dashboard is accessed or refreshed in UI, it will fetch the latest data.
6. Free of Cost
Data Studio is offered free of cost at this point and is bundled with Google cloud services. The storage cost for data and processing costs for transformation is outside of this.
There are two ways to connect to the Google Data Studio.
- Natively supported: Google Analytics, Google Ads, Google Sheets, Google Ad manager 360, Youtube Analytics etc.
- Third-party/partner connectors: Appnexus, Bing Ads, BirdEye, AmazonSeller, Asana etc.
Which graphics should be used when?
- Line charts: Best when you want to emphasize a trend.
- Bar/Column charts: When you want to show the difference or a comparison
- Area Charts: To show the differences over a period of time.
- Pie Charts: When you have minimal items and you need to show something very simple without any comparison
- Sparklines & Scorecards: To add context to data points without a large use of the real estate.
- Pivot Tables: When you want to show two dimensions by each other.
- Maps: When you want to depict a story with the help of the data
Why Do Pie Charts Fail?
- The human brain can’t judge the size difference in an area very well.
- People use too many pieces.
When Are Pie Charts Okay?
- When you have minimal items (preferably 3)
- They must be parts of a whole
- You only get one (no comparisons)
Use of Colour in GDS:
Colour formatting in the visualization can have a different perspective on the visualization model. Usage of the colour should be wise.
When you have multiple dimensions, there are two options that you can use:
- Series Order: Colours are based on the order of the series and your sort order.
- Dimension Value: Colours are based on the value of the dimension itself. (For example, the desktop will always be blue, mobile will always be red.)
Chart Settings:
- Metrics: By default, the metric or dimension name in use might be long and difficult. A good practice is to be clear, concise and brief with the names.
- Data Labels: You can add data labels and adjust the label font size. The axis and data labels can be repetitive, so it may be a good practice to hide one.
- Legend: A good practice can be to use a shared legend to avoid clutter. Avoid using legend all the time, consider pixel to data ratio here.
Data Blending
Data blending is Google Data Studio’s version of a join.
- You can blend up to five sources.
- Blends are always a left join.
Creating a Blend
- Select multiple charts, make right click and select “Blend Data”.
- Or select “+” blend date under the data sources
Preserving Calculated Fields
- Copy the data source
- Edit the connection
Google Sheet Annotations: It is a Google Chrome Extension and with that extension you can add notes like date, comments to your dashboards on Google Data Studio.
Conclusion
Considering all these features, Google Data Studio provides us with very important things to visualize and understand data better. The features and the things it can do are increasing day by day.
Many factors such as being free of charge and being open to innovations increase the use of Google Data Studio day by day. In addition, being able to install other 3rd party applications outside of Google products increases the use of Google Data Studio among analysts and marketers.
See you next week with a new blog post containing details from the CXL digital analytics mini degree program.
Thanks,
Mert Kolay
