Data Lineage”: Reduction of Risks & Governance

 

“Data Lineage”:   Reduction of Risks  & Governance Data lineage represents the complete traceability of data, from their origin to their final use.   It provides a detailed view of data flows, identifying transformations and dependencies. The implementation of data lineage has often been motivated in the banking world by compliance requirements such as those of BCBS239, the data component of Basel III aimed at strengthening the capacities of banks in terms of production and reliability of reports of risk. Indeed, the 2008 crisis highlighted the lack of reliability in the most structuring risk reports.   But data lineage offers possibilities that go far beyond this framework:  more effective risk management, optimization of information systems, etc., thus opening the way to numerous use cases. However, to have the expected added value, the data lineage must be an exact reflection of the information system in real time. And it must offer different reading levels to allow everyone to benefit from it in line with their needs. Data lineage  and GDPR With the advent of the new personal data protection framework (GDPR), precise mapping and reinforced controls over processing involving personal data are now essential.   From this perspective, data lineage presents itself as a facilitator. It makes it possible to represent the different data production processes, It also enables the identification of processing errors in chains that can include countless processes, thereby reducing the risk of non-compliance with personal data. Especially since investigations can be triggered very simply by teams without technical knowledge.   Data lineage and data governance   The implementation of data lineage offers the entire organization a detailed repository, describing data flows, as well as a shared vision of the system architecture, thus promoting the development of effective data governance and a data quality strategy.   This in-depth knowledge of the system is also very useful for optimally architecting projects:  By highlighting strategic flows and all their dependencies. By offering a valuable tool for the design of an optimal architecture through the simplification of information systems : in fact, data lineage coupled with the definition of information uses makes it possible to identify unnecessary data flows in systems information, prior to large-scale decommissioning operations.  Data lineage and operational improvement In a complex environment, investigation work on the data assets, and the assessment of the impacts of this or that modification on the entire system can prove tedious.   Automating data flow documentation can significantly reduce these workloads. And as data enhancement projects become more and more strategic, a thorough understanding of data flows becomes an essential element for success. Especially when this understanding is shared as widely as possible.    Data lineage also proves to be a valuable tool for IT support teams. It facilitates the analysis of malfunctions and the implementation of fixes, thus enabling faster resolution of production incidents and a reduction in service interruption times. Data lineage, prerequisites Different technical data lineage solutions exist, making it possible to represent data flows on both a technical and business level. But to ensure the value and sustainability of the approach, the data lineage must be continually updated according to developments in the information system . Automation of analysis processes must be a prerequisite. It will be necessary to ban any manual action to avoid decorrelating the vision of flows from their concrete reality. In short, data lineage cannot be an Excel sheet filled in piecemeal!     Furthermore, the regulatory or technical approaches within a company are not the same. The data lineage must be able to offer different angles: A fairly broad vision allowing a flow to be documented in one piece, for internal sharing or to the regulator. And a detailed vision allowing us to investigate the technical reality of transformations, from operational sources to the dashboard cell. As such, data lineage must be capable of analyzing disparate technical architectures and addressing the innumerable technical breaks in the flows.   Conclusion    In short, data lineage turns out to be a major asset for all organizations with complex data processing processes. It not only represents a lever for improving operational efficiency, an essential tool for risk management and an essential element in the implementation of an effective data strategy.  But it must meet precise technical characteristics : be exhaustive in the variety of technologies processed, it must be perfectly automated and it must offer different approaches to meet business needs on the compliance side, but also IT, on the governance side.   Ellipsys is the vendor of {openAudit} , a data management software  which has been chosen by many banks and other types of players in Luxembourg (and elsewhere in Europe). Technical and multi-technological data lineage is one of the most differentiating components.    contact@ellipsys-lab.com  www.ellipsys-lab.com