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How to Calculate EBITDA in Redshift

Making the most of your Redshift data

What is EBITDA?

EBITDA is an acronym for Earnings Before Interest, Taxes, Depreciation and Amortization. It is a measure of a company's operating profitability, and is often used in the financial industry to determine the value of a company.

EBITDA is calculated by taking a company's earnings before interest, taxes, depreciation and amortization, and adding back interest, taxes, depreciation and amortization.

EBITDA is a great metric to use when determining the value of a company, because it is a measure of the company's ability to generate profit.

How do you calculate EBITDA in Redshift?

It can be difficult to calculate EBITDA directly inside of Redshift; that's where Causal comes in.

Causal is a modelling tool which lets you build models on top of your Redshift data. You simply connect Causal to your Redshift account, and then you can build formulae in Causal to calculate your EBITDA.

What is Causal?

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 EBITDA. This makes your models easy to understand and quick to build, so you can spend minutes, not days, on your models.

A comparison of formulae in Excel and Causal

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.

A gif showing how users can adjust model inputs, and how they're reflected in dashboards

Causal lets you add visuals in a single click, letting you plot out graphs and distributions for metrics like EBITDA.

A gif showing how you can build visuals in Causal

Start building models with your 

Redshift

 data

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