Case Study

Data Governance & Lineage

An emergency services organisation operating within a highly regulated and complex environment, had very limited data controls in place, partly due to aging systems. There was an extensive need to understand data usage and improve decision making, but without data ownership the data could not be trusted.

Opportunity

There was an opportunity to reduce the risk of sensitive patient data being used for the wrong purpose, by providing visibility over data usage and implementing controls across the organisation's data flows. This would realise improvements to the quality of data and the accuracy of reporting, while also making data ownership more effective. Being more data aware and having better insights into operations, helps move decision making from being based on opinions to being based on experience + facts.

Hypotheses

Is it possible to scan & track datasets as they flow throughout a supply chain, including operational usage?
Is it possible to overlay regulatory, legal and security controls onto datasets within data flows?
Is it possible to get executive ownership of data, if data is modelled as data products?
Is it possible to understand the lineage of data?

The solution

Understand the current state by running a series of discovery sessions to assess data usage across operations. Designed a set of data products and training material for data owners and stewards. This included understanding the supply chain, the data flows, and regulatory, legal and security controls. Following the technology selection, a series of proof of concepts were ran to evaluate the approach and agree the design for full implementation.

Outcome

This resulted in a new set of data products and associated controls for a data governance forum that drove executive ownership. Including improved visibility over data flows and an approach to overlay controls and tracking capabilities that were found to reduce the risk of inappropriate data usage. The technology uncovered a large number of vulnerabilities and data quality issues, driven by how data was entered into various aging systems and where the data was subsequently being used. Data handling improvements were also realised through upskilling operational staff, but understanding data lineage over the lifecycle of data was out of reach for the solution.

Technological Change Consultancy

CONSULTING FROM REAL EXPERIENCES

Case Study

Data Governance & Lineage

Opportunity