Data Transformations Using the Data Build Tool

At Ripple, we are moving towards building complex business models out of raw data. To do this successfully, we need to automate our historically manual processes. Even with a digital-first approach, many of our internal processes were done by hand, making them great candidates to be automated. ... Read More

Building CI/CD with Airflow, GitLab and Terraform in GCP

As the Ripple Data Engineering team expanded it needed to programmatically enforce software engineering best practices. The team created a CI/CD pipeline that automatically validates and tests new features for data applications in Google Cloud Platform (GCP). ... Read More

Liquidity Monitoring: Depth

In our last liquidity monitoring post, we introduced the concept of dislocation as a way to measure the price competitiveness of an XRP-fiat pair. In this post, we introduce the companion depth metric and combine both metrics into a data visualization for assessing liquidity performance. ... Read More

Liquidity Monitoring: Dislocation

We wanted a way to tease apart these distinct effects, so we decoupled our analysis in terms of dislocation and depth of liquidity at exchanges. In this post, we introduce the dislocation metric. ... Read More

Quantifying the Environmental Impact of Payment Systems: Part 2

In part 1 of our series, we discussed the motivation and framework behind measuring the environmental cost of a payment transaction. We also talked about the methodology for credit card networks. In this post, we continue to cover the environmental impact model for Cryptocurrencies and paper money. ... Read More