Data Tracing

What is data tracing?

Data tracing refers to being able to trace back from a critical business use case, such as an annual report or compliance requirement, to see the source, journey and changes of data that impact these use cases. Data traceability across all business systems is important for accuracy, confidence, and compliance of data.

Data tracing vs. data lineage: What’s the difference?

Data tracing requires data lineage in place initially. Data lineage represents the journey of data as it travels from source to destination. This journey encompasses the entire lifecycle of data, detailing where it enters a business, how data flows through various processes and systems, how that data is subsequently transformed – through calculations and formulas for example – and where it is then used in critical ways in the business, such as for decision making, reporting, AI, regulatory compliance and much more. Once data lineage is in place, it enables data traceability, allowing you to identify any piece of data and trace where it is used back to its source.

Can GenAI be used for data tracing?

GenAI can help infer or make assumptions when the full end-to-end data lineage is not in place. It can help generate lineage in certain circumstances or search, comment on, or summarize findings from data itself. For example, one might want to know, “Do I have any data quality issues on this trace?” Once the lineage is in place, GenAI will show you the answers, but not the order or the transformations.  Our data lineage solution fulfils this level of detail.