Return on Assets (ROA) is a financial ratio that measures a company's profitability. It is calculated by dividing a company's net income by its total assets.
Return on Assets is a good way to determine how efficient a company is at generating profit from its assets.
Return on Assets is a useful metric for comparing companies in the same industry. It's also a good way to determine whether or not a company is generating a profit from its assets.
If a company has a high ROA, it's a good sign that the company is generating a profit from its assets. If a company has a low ROA, it's a good sign that the company is not generating a profit from its assets.
It can be difficult to calculate Return on Assets directly inside of Google BigQuery; that's where Causal comes in.
Causal is a modelling tool which lets you build models on top of your Google BigQuery data. You simply connect Causal to your Google BigQuery account, and then you can build formulae in Causal to calculate your Return on Assets.
Causal lets you build models effortlessly and share them with interactive, visual dashboards that everyone will understand.
In Causal, you build your models out of variables, which you can then link together in simple plain-English formulae to calculate metrics like Return on Assets. This makes your models easy to understand and quick to build, so you can spend minutes, not days, on your models.
When you're done, you can share the link to your model with stakeholders. They'll be able to view your model's outputs in a visual dashboard, rather than a jumble of tabs and complex formulae. The dashboards are interactive, letting viewers tweak your assumptions to see how they affect the model's outputs.
Causal lets you add visuals in a single click, letting you plot out graphs and distributions for metrics like Return on Assets.