In this article, Daniel Waisberg will show a mobile dashboard example and provide the steps to build your own fit tracking dashboard. Mobile dashboards' goals are usually to track daily metrics to monitor performance - those visualizations that people might need to access in their way to work on their phones.

Data is the new coal. Data is sexy! Data is controversial and (surprisingly) exciting. Everyone loves data. Everyone wants data. Now!

Learn how to tackle fraud while working in CPA networks, as well as how to avoid extra expenses on affiliates.

In this article Daniel Waisberg discusses some thoughts on the US opioid crisis and how it compares to the worldwide drug adoption and overdose rates. He presents a Data Studio visualization with trends and patterns related to drug usage and adoption

Data is important. In this article from Phil Harvey, Data Philosopher, you will learn why it gives us new things to know and new ways of knowing this.

In this article, Daniel Waisberg presents 8 great visualizations created with Google Data Studio: four visualizations for business contexts and four for journalistic stories.

In this interview, Daniel Waisberg talks to Feras Alhlou about making sense of data, from the very start to making a business impact.

In this article Daniel Waisberg provides more context into GoalKeepers 2017 using publicly available UNICEF data on maternal mortality. He discusses important points from the GoalKeepers 2017 report - then, he discusses some of the steps he used to create his report and the insights he learned from the data.

In this article, Daniel Waisberg, Analytics Advocate at Google, shares insights on how to embed Google Data Studio reports on articles to create effective data stories.

In this article Georgi Georgiev discusses the misuse of statistical significance tests, the lack of consideration for statistical power, and the significant inefficiency of statistical methods. He proposes solutions to those issues inspired by clinical randomized controlled trials, which I call the AGILE statistical approach to A/B testing.