Intro

I had an idea to conduct experimental training on working with Google Data Studio for marketers, product managers, and SEOs. As a rule, this tool is considered in one of the training units on web analytics, digital marketing, or as part of a course on Google Analytics. But as a rule, they pay little attention to Data Studio and do not consider filling all important possibilities of this visualization tool.

Yes, there is a course for beginners at Google Analytics Academy. You also can find some courses on Udemy and similar education platforms. But I think these courses educate how specific features work in Data Studio, but don’t explain how to use them in different cases.

Data Studio is a universal assistant for anyone working with data: web and product analyst, SEO specialist, PPC specialist, internet marketer, project manager, product manager, financier, and others. But each role has different jobs to be done and needs a specific approach to education.

The idea came up, but I don’t know how much demand there is in the market for such training. So, I need your feedback. You can research which Google Data Studio Templates I created and make a decision based on that. If you are interested in such a course, write me via chat or email ivanpalii [at] ivanhoe.pro.

Important! This course is only suitable for active professionals who already have experience with any data. Ideal if you have at least one of the basic tools: Google Sheets, Google Analytics, Google Search Console, Google Ads, Facebook Ads, YouTube Analytics.

Google Data Studio Course Program

  1. Opportunities and challenges of Google Data Studio.
  2. Comparison of Google Data Studio with other data visualization tools (Microsoft Power BI, Tableau).
  3. The evolution of mastery in Data Studio. From using ready-made reports to creating your own reports for any task.
  4. The main preparation problem: you need to understand the parameters and metrics of a specific data source.
  5. Google Data Studio connectors.
  6. Creation of a report in real-time (metrics, parameters, filtering, segments, import from tables, chart types, style settings, sorting, periods, combining data from several sources, creating custom metrics and parameters).
  7. What charts and for what jobs to be done to use. Key principles of data visualization.
  8. Why reports, charts can break? Popular issues. Data Studio limitations. The frequency of data refresh.
  9. My ready-made SEO and web analytics reports: how to use them correctly.