Data Visualization is the cherry on top of the data world, it makes information useful and meaningful. By using best practices when creating bars, lines and pies, you will be able to enlighten people not only in your workplace, but also through external analysis of publicly available datasets.
As a comic book fan, Daniel Waisberg decided to look at publicly available data to understand which movies in the MARVEL and DC cinematic universes succeeded from a monetary perspectives. Hold your breath!
In this article Daniel Waisberg provides a step by step guide on how to use Data Studio. He focuses on how to access / transform / manage your data and how to visualize / collaborate / share it.
This article is a quick overview of the Search Console data connector for Data Studio. Daniel Waisberg discusses all metrics and dimensions available and brings them to life with examples.
In this article, you will learn how to use Google's Data Studio and BigQuery to create your own dashboards, using an example created to visualize 2016 Election Cycle Donations, exploring public FEC data curated by OpenSecrets.org.
In this article Daniel Waisberg presents a visualization using data from the US Bureau of Labor Statistics to show trends in US Unemployment Rates segmented by Age, Gender and Race / Ethnicity.
This article shows you just how simple it is to connect Google Data Studio to Google Analytics and from there, indicates how to really make the most of Data Studio's fantastic data visualization and reporting features.
This article shows examples of dashboards that can be updated in real time and used by marketers, developers, content-managers and even analysts (!) in Ecommerce projects.
in this article Daniel Waisberg shares beautiful charts from real Google Analytics data, focusing on both symmetrical shapes and interesting patterns.
In the presentation below shown in the article Daniel Waisberg summarize the process of going from data to insights with a six step framework he has been using for the last year.
This article is a step-by-step guide on how to visualze Google Analytics data using the R programming language, a powerful statistical language. It provides both the the code necessary to do so and the explanations on how to make it work.