The trouble with a Sankey diagram is its scalability. A Sankey Diagram produced by the World Resources Institute summarizing greenhouse gas emissions in 2016 These days you can find Sankey diagrams representing anything from supply chain and commodity movements to the shifting political allegiances of voters. Sankey, who first used it to represent the thermal behavior of steam engines in 1898. One of the most famous visualizations is named after M. So how do we represent flow in a way that investigators and analysts can understand? There’s a well-established visualization style you may be familiar with already… The Sankey solution modeling a cyber attack based on its path through an IT infrastructure.understanding criminal activity by tracking the paths taken by illegal movement of people, drugs or arms.tracking the spread of something across a population, such as a rumor or a virus.tracking cryptocurrency payments and transactions.Investigators across many domains use event, activity and commodity flow analysis to establish behavioral patterns. Flow analysis: a crucial investigative technique So why is it so important to understand flow? Let’s look at some popular use cases. For example, a single bank transfer between an account owned by Company X and an offshore bank account. A transaction is an individual, atomic event connecting a source to a destination. For example, a net flow of ten million dollars between the accounts owned by Company X and offshore banks.įlows aren’t the same as transactions. Think of flow as a summary of the net movement of a quantity, formed by aggregating transactions, sources and destinations in a way that tells you something useful about the system in question. The best analytical tools make it easy to investigate flow, not just examine individual transactions What do we mean by flow?
In this blog post, we take a closer look at how applications built with our data visualization tools give you a clear picture of flow, with examples from financial fraud investigations, cyber security and cryptocurrency. That flow could represent funds, data, commodities, information and more. But another level of understanding emerges when you combine these transactions into a bigger picture – understanding the overall flow between participants. Most of the connected data we work with involves a soup of individual transactions, from financial payments to telephone calls.